deploying predictive analytics, innovation
DESCRIPTION
In this presentation Rainer Dronzek talks about deploying the use of predictive analytics with the help of the innovation team. Dronzek discusses why McDonalds are looking into using predictive analytics, and how they are aiming to deploy it with the help of their new and improved innovation teams and centres.TRANSCRIPT
Deploying Predictive Analytics
Rainer DronzekOperations Research
Restaurant Innovation11/3/11
Operations ResearchThe Science of Better
McDonald’s Today
• 60 million customers per day • 32,000+ restaurants in 100+ countries• 81% franchised• 5,000+ Owner/Operators• 1 5 million system employees1.5 million system employees• Major geographic segments:
o U.S.o Europe
Remodeled 5,000 restaurants around the world during the o Europe
o APMEA (Asia, Pacific, Middle East, Australia)
o OCC (Canada Latin America and
grecessionary years of 2007 to 2009
In 2010, spent approximately o OCC (Canada, Latin America and Corporate)
• $60+ Billion system-wide sales
, p pp yhalf of $2.4 Billion capital expenditure budget on remodeling 2,000 additional restaurants
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restaurants
1970s-1990s: Innovation Exporter
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Today: Innovation Network
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Innovation Center
Accelerate learning, inspire thinking,
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promote continuous improvement and integrate new ideas
Innovation @ McDonald’s
A Factory for Inspiration & Profound Knowledge
Development & TestingDevelopment & Testing o Componento System
Area of the World Support o Testingo Testingo Modeling o Projects
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The Innovation Team
A diverse mix of technology, engineering, operations, operations research and design development staffp g p
Innovation staff reveal our newly designed High Density UHC to the Europe Service and Russia team
Operations ResearchThe Science of Better
Innovation staff reveal our newly designed High Density UHC to the Europe Service and Russia team
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Innovation Center
Lab TestingPrototyping
Development
Operations Research
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Reconfigurable Kitchens
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Lab Testing
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Consumer Behavior
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Operations Research
• Advanced & predictive analyticsVid l i & th h• Video analysis & ethnography
• Engineered standards• Laboratory testing support• Laboratory testing support• Internal consulting services Screen shot of our Drive-Thru Simulator
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Some of Our Data Sources
• Global Data Warehouse• Point of Sale (POS) transaction-level detailPoint of Sale (POS) transaction level detail• Supply chain partner data• Third party store-level data analyticsp y y• Third party data sets (e.g., trade area, demographics)• ROIP – Restaurant Opportunity Improvement Program• Data and reports from Areas of the World and
countries• Quick service restaurant (QSR) research and ranking• Quick service restaurant (QSR) research and ranking
agencies• Research data – customer experience, crew behavior,
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operations, marketing11/3/11 Page 13
Why Simulation-Based Predictive Analytics?
• Analyze system and restaurant-specific data to understand the impact of existing and potential changes across the systemo Equipmento Staffingo Menuo Customer behavioro Customer behavioro Site conditionso Rules and procedures
• Use models to further predict how conditions impactUse models to further predict how conditions impact performance
• Use simulation models (Simulators) to analyze and communicate
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Why Deploy?
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Simulator Demonstration
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Our Approach to Simulator Deployment
• Market-specific Simulators account for differences in o Order size, complexity, and product mix; terminology, , p y, p ; gy,
currency; equipment and facility configurations; labor laws
• The Simulators allow users toSimulate various in store and drive thru configurationso Simulate various in store and drive-thru configurations
o Run scenarios using a range of operating conditionso Report performance in terms of sales, guest counts, lost
t tili ti d t icustomers, crew utilization and customer experienceo Visualize operations to help communicate concepts & results
• Three versionso Basic, web-based application – easily deployableo Advanced, adds scenario management and reporting
Expert for discovery and research
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o Expert, for discovery and research
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Our Approach to Simulator Deployment
• Centralized subject matter experts• Embedded Simulator points of contactEmbedded Simulator points of contact• Global Service Team governance• Formal processes forp
o Releaseo Configuration controlo Change managemento Change managemento Support
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But There’s More …
• In some cases the message is more important than the Simulator
• So, deploy message tools along with analysis tools• The Simulator Viewer …
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Operations ResearchThe Science of BetterThank You