Business Intelligence: Advanced Analytics in Competitive Environments

Transcription

1 Business Intelligence: Advanced Analytics in Competitive Environments Tuesday, June 22, 2004

2 YOUR MISSION CONDUCT RECONAISSANCE GATHER INTELLIGENCE DISCOVER SECRETS UNCOVER THE TRUTH LOOK CLOSER ALL IS NOT AS IT MAY SEEM

3 Mission Agenda Dossiers: Agent Introductions BI Classified Agent Interrogation Mission Objectives Debriefing <Case Studies> Beyond Business Intelligence Audience Interrogation

4 Mission Objectives Define meaningful information requirements Evaluate modern tools that support them Understand the relationship between quality of data and improved forecasting Identify and respond to competitive opportunities and threats Develop advanced guest intelligence Real-time verses right-time analytics and response capabilities

5 GET SMART!

6 DOSSIERS <AGENT INTRODUCTIONS>

7 Agent M. Dober Agent L. Phillips Agent G. Verma Agent E. Ivey (Interrogator)

8 BUSINESS INTELLIGENCE CLASSIFIED

9 BI Exposé Business intelligence (BI) applications are decision support tools that enable real-time and interactive access, analysis, and manipulation of corporate information. {Marketing, revenue, yield, transactional, ancillary services, customer behavior, booking trends, asset maintenance, key performance indicators, expense ratios, and/or employee productivity data}

10 Secret to Successful BI Missions Requires a coordinated effort across many dimensions People Process Technology Data

11 BI Benefits Leverage information from multiple sources and operating entities Enable personnel to make more accurate, timely, repeatable business decisions across the organization and not just selected functions Minimize decision costs associated with: Poor decision making capabilities Slow decision making processes Inaccurate core data Wrong people empowered to provide critical info

12 BI Benefits continued Accessibility and visibility by the masses to transactional and operational data in order to understand trends and analyze relationships Provide intelligence on every desktop to target and empower the right people with the right information

13 Defining BI Defining Business Intelligence Globalization Business Specialization Information Delivery Data Mining and Analytics Data Management Integration Security Performance

14 Buyer Decision Drivers Typical Information User Model Aggregate Information via a dashboard or portal Executive In the hospitality industry in most cases an Army of One Power / IT User Slice & Dice and Report Generator at the Data-Level In the hospitality industry in most cases unaware of what to do with the information General User Information Consumer via Reports or Actionable Tasks

15 Market Landscape Vendor Landscape Niche Applications Datavision Technologies HIS Cognos MicroStrategy ApTech Business Objects (CD) SAS Dimensional Insight Hyperion (Brio) SPSS Oracle Enterprise Applications Siebel SAP Data Warehouse Vendors Database Vendors Informatica SAS IBM Oracle Group 1 SAP Informix Sybase Clairvoyix Teradata Microsoft

16 AGENT INTERROGATION:

17 MISSION OBJECTIVES:

18 Meaningful Information Requirements Defining meaningful requirements is dependent upon business strategy and operational objectives Real estate investment drive revenues and maintain the asset and competitive position Multi-brand management company - drive revenues, leverage brand resources, control expenses, centralize administration Luxury/service oriented properties please the guests, keep the most profitable ones returning, anticipate changes in consumer expectations and maintain the asset

19 Data Quality & Forecasting More than a quarter of critical information at Fortune 1000 companies is considered inaccurate or incomplete. Data quality problems are most often responsible for the failure of business intelligence and CRM initiatives Source: Gartner Group A surprising number of people spend the equivalent of a full work day per week trying to find electronic information. Large majority are dissatisfied with their search experiences. Source: Delphi Group Throwing technology at data quality issues will not yield positive long term results.

20 QUALITY OF DATA AND DATA FLOW Old Data Flow PMS PMS Re-keying B-O PMS New Data Flow PMS PMS PMS Business Intelligence B-O

21 Responding to Opportunities & Threats Leveraging changing market dynamics using an intelligent and rapid decisioning process Mitigating risk through recency and frequency of assessment of exposure to the business Embedding logic that helps preserve knowledge capital, at risk with high turnover, in perpetuity Creating a culture of intelligence gathering and knowledge seeking

22 Advanced Guest Intelligence OUTWIT OUTPLAY OUTLAST Raw Intelligence Application Consistency DATA Standardized Codes Naming Conventions Mapping/Look-up Tables Top Secret

23 Advanced Guest Intelligence Data Enhancements Domestic (in-house) New Data Dimensions Foreign (third party) ICS Data Applications Domestic/Foreign Multiple Views NOT Multiple Sorts Campaign Management Trend Analysis New Business Opportunities Predictive Modeling

24 Advanced Guest Intelligence COMBINED YEARS # OF GUESTS % # OF VISITS % 1 VISIT 91, % 91, % 2 VISITS 9, % 18, % 3 VISITS 1, % 5, % 4 VISITS % 2, % 5 VISITS % 1, % 6+ VISITS % 3, % TOTAL 103, % 123, % ONE VISIT GST 91, % 91, % REPEAT GST 12, % 31, % OVERALL REPEAT 103, % 123, % What s our repeat %?

25 Advanced Guest Intelligence CAMPAIGN CAMPAIGN DESC DAY/ DATE SENT START DATE END DATE SUBSET CONTACTS RESP/ VISITS CONV % TOTAL $ COSTS NET $ AFTER COSTS NET $ PER CONV 2004 SPRING SOCIAL SPRING SOC MAIL GIFT CARD 1/22/04 3/14/04 5/26/04 Total EX_04 SPRING 03SOC GSTS 11, % $287,106 $10,110 $276,996 $1,466 EX_04 SPRING 02_03 SPRING GRP 4, % $153,883 $4,410 $149,473 $895 EX_04 SPRING 01_02 SOC GSTS 15, % $160,412 $14,210 $146,202 $1,392 EX_04 SPRING 03 GLF ADMY 2, % $147,188 $1,788 $145,400 $1,580 EX_04 SPRING 03 INQS DD 7, % $43,467 $6,297 $37,170 $1,487 EX_04 SPRING 99_00 SOC GSTS 6, % $44,938 $6,068 $38,870 $1,944 EX_04 SPRING 04 INQS DIR 2, % $8,477 $2,127 $6,350 $1,058 EX_04 SPRING 03 INQS MAG % $0 $441 -$441 $0 EX_04 SPRING 03 INQS MAG % $0 $37 -$37 $0 EX_04 SPRING 03 INQS MAG % $0 $36 -$36 $0 EX_04 SPRING 03 INQS MAG % $0 $315 -$315 $0 EX_04 SPRING 03 INQS MAG % $0 $161 -$161 $0 51, % $845,471 $46,000 $799,471 $1,324 Did that direct mail campaign work?

26 Advanced Guest Intelligence Nielsen DMA VISITS RM NTS TOTAL $ AVG LOS AVG VISIT $ AVG RM NT $ 1 NEW YORK $175, $1,740 $756 2 RALEIGH - DURHAM (FAYETTEVILLE) $37, $621 $468 3 CHARLOTTE $40, $763 $512 4 WASHINGTON DC (HAGERSTOWN) $57, $1,924 $843 5 PITTSBURGH $33, $1,413 $547 6 HOUSTON $34, $2,174 $693 7 GREENSBORO - HIGH POINT - WINSTON-SALEM $28, $962 $658 8 PHILADELPHIA $29, $1,756 $702 9 CHICAGO $28, $1,930 $ ATLANTA $21, $978 $ BOSTON (MANCHESTER) $41, $2,054 $1, CLEVELAND $16, $942 $ RICHMOND - PETERSBURG $16, $1,465 $ KANSAS CITY 8 23 $13, $1,638 $ LOS ANGELES 6 18 $17, $2,930 $ DALLAS - FORT WORTH 8 17 $8, $1,098 $517 GREENVILLE - SPARTANSBURG - 17 ASHEVILLE - ANDERSON 7 17 $7, $1,129 $ MIAMI - FORT LAUDERDALE 5 16 $10, $2,105 $ BALTIMORE 7 15 $10, $1,511 $ DETROIT 8 14 $9, $1,245 $711 All Others $204, $1,474 $682 Totals 604 1,239 $845, $1,400 $683

27 New York MSA Block Level (1) Market Potential <5% Advanced Guest Intelligence

28 Advanced Guest Intelligence WEEKPART VISITS RM NTS TOTAL $ AVG LOS AVG VISIT $ AVG RM NT $ Extended $91, $2,959 $760 Midweek $480, $1,279 $641 Weekend $272, $1,386 $742 Totals 604 1,239 $845, $1,400 $683 MEAL PLAN VISITS RM NTS TOTAL $ AVG LOS AVG VISIT $ AVG RM NT $ BB $14, $466 $318 EP $39, $532 $293 FAP $112, $1,684 $598 MAP $678, $1,577 $781 Totals 604 1,239 $845, $1,400 $683

29 Advanced Guest Intelligence Fiscal Period/ Year 0-7 Days 8-14 Days Days RM NTS % of RM NTS RM NTS % of RM NTS RM NTS % of RM NTS Days Days Days RM NTS % % % % 0.0% 0.0% % % % % % % 0.0% % % % % % % % % % 8 9.4% % % % 8 9.4% % % of RM NTS RM NTS % of RM NTS RM NTS % of RM NTS RM NTS Totals % of RM NTS Total % % % % % % 1, %

30 Real Time vs. Right Time What many vendors call real-time is real-time access to historical analytics Historical Analytics Real-Time Analytics Predictive Analytics Business Intelligence Information Delivery Data Mining & Analytics Data Management Data Warehouse Data Mart Operational Data Store OLTP T 1 T 1/2 day T 1 hour T T + 1 T + 2 T + 3 Latency Factor

31 AGENT DEBRIEFING <CASE STUDIES>

32 DEBRIEFING CHS-Clairvoyix Corporate Hospitality Provides/Applies: data cleansing, householding, data enhancements, calculations, business rules, etc. All about the guest -returns only guest/customer counts Queries the data Boolean Logic Generates lists for traditional mailing and campaign fulfillment Tracks direct marketing communication Campaign management Provides preformatted reports

33 DEBRIEFING

34 DEBRIEFING Dimensional Insight OLAP Tool Stand alone robust business analyzer Data Models/Cubes Enhanced ad hoc reporting Complete report flexibility Numerous views of the data Drill up/drill down Allows for grouping of like data Report Writer/Graphs

35 DEBRIEFING

36 DEBRIEFING Developing a successful business plan around technology initiatives Determine your strategic goals for investing in a BI solution Develop a comprehensive enterprise BI strategy Complete a BI gap analysis

37 Barriers to BI Adoption in the Hospitality Industry Budget Constraints Belief that operational systems provide adequate metrics Misconception that EIS/reporting equals analysis Lack of detailed operating data; inability to extract from older, proprietary database structures Lack of integration; poor data relationships due to disparate transactional systems Data-phobic users Change management

38 BEYOND BUSINESS INTELLIGENCE:

39 Evolving Business Intelligence Shifting Focus to Business Performance Management A closed-loop process that facilitates strategic organizational planning, monitoring the performance of these plans and analysis of issues for maximum effectiveness of the plan Ultimate Goal of Knowledge Management The conscious and comprehensive gathering, organizing, sharing and analysis of knowledge capital by an organization Walk before you run There is a natural evolution from BI to the more sophisticated practices of BPM and KM Without successful BI initiatives, the transition to BPM and KM will be very difficult

40 Provider Trends BI Trends Not just real-time access, but true real-time analysis Developing Web services-user friendly architectures Packaged applications for rapid implementation and industry practice awareness Data management as a fundamental part of the implementation Packaging a portal Placing bets on machine-to-machine interfaces Increased emphasis on usability by variety of users Continued consolidation among technology providers

41 AUDIENCE INTERROGATION

42 MISSION ACCOMPLISHED THANK YOU FOR YOUR COOPERATION