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Analytics

Transcript: CheeseCake Factory Inventory (Beginning inventory + purchases) – Ending Inventory = Usage) -Organize Your Restaurant Inventory -Count Your Inventory -Calculate Usage -Determine Your Order Once you figure out the average usage for each item in your inventory, you can easily determine how much to order. -Importance: Potential loss of $$$ -Data: Measuring total labor hours compared to total traffic -Decide: -Overstaffed? -Understaffed? -Correctly staffed? Operation Hours -Importance: Losing money on a controllable issue. -Data: Measuring success nearing the opening and closing times -Decide: -Open later? -Close earlier? -Leave as is? Marketing Effectiveness Dishes Ordered per Table Customer Satisfaction -The Customer is Always Right -Simple After-Meal Survey -Provides Important Feedback and Demographics Wait Time -For a Table, Food, Water Glass Refill, Total Time Spent at the Restaurant, and Time of Arrival -Hire an Observer to Collect Data Nationwide. -Create a Restaurant That Is: -More Efficient -More Reflective of Customer’s Preferred Eating habits -Keep a record of how many tables have purchased alcoholic beverages based on their check. -Keep a detailed record of which alcohols are most commonly ordered as well as soft drinks -In order to improve promote specials of those most popular items -Monitor gross profit and turnover Measuring desert and appetizer orders -Keep tabs on all items ordered besides main course items -Check and see which items sell the most and to what types of people -Have a few specialty deserts and appetizers that serves can recommend while the client is ordering -Monitor waste and stock turnover Measure customer loyotality Overstaffing vs. Understaffing Bar & Cellar Management

Analytics

Transcript: Twitter followers Thank you http://www.fivethirtyeight.com/2008/03/frequently-asked-questions-last-revised.html http://strata.oreilly.com/2012/01/what-is-big-data.html http://radar.oreilly.com/2011/09/building-data-science-teams.html https://twitter.com/SamWangPhD http://krugman.blogs.nytimes.com/2013/10/08/the-midterms-sam-wang-weighs-in/?_r=0 http://www.dnaindia.com/bangalore/report-big-data-crunching-is-the-new-job-creator-1887375 https://twitter.com/dpatil Accumulate and analyze polling and political data from hundreds of sources generated on a daily basis in a way that is informed, accurate and attractive Meet Patil Saheb writer, analyst and partner at a sports media company called Baseball Prospectus Analytics ...Velocity No of electors in the US Presidential electoral college Variable 635,803 50k insider Sam Wang Neuroscientist, Professor. Founded the Princeton Election Consortium - polling meta-analysis since 2004. Irony WHO CARES? Volume Predicted all states correctly Starting salaries LPA Variable Fill in the Blanks Percentage of states (49 out of 50) where he predicted the outcome of the US Presidential elections correctly 538 Firstly, Weighting by reliability. Secondly, regression estimate based on the demographics. Thirdly, inferential process to compute a trend. ‘current scenario’. Even where no recent elections have happened Fourthly, we simulate the election 10,000 times Velocity 4 8-14 jobs in India in next 2 years Why bother? 4 things you need to be an How will you take advantage? 1. Polling Average 2. Trend Adjustment 3. Regression 4. Snapshot: Estimate of what would happen if the election were held today. 5. Projection: What will happen in the election 6. Simulation: Simulate our results 10,000 times 6 50 Attention to detail Big Data, Big Advantage. Big Deal? Highest Rank on Amazon non fiction Repeat until numb Ifferent ers make sense O Steps Intelligence In His own words... ? ` If you smiled, this presentation is for you Compile data from everybody ELSE's surveys the ability to look at a problem in different, creative ways. Going up to LPA No guarantees, though.... Gaurav Vohra - Jigsaw 98 Nate D Data Science Amit Chatterjee - HP 4,183 Twitter Followers Volume Technical expertise Curiosity Storytelling Cleverness: 5-9 Nathaniel Silver

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