Empower Mobile Restaurant Operations Analytics with Oracle business Intelligence and Endeca


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Multi-unit, multi-concept restaurant companies face challenging reporting requirements.

How should they compare promotion, holiday, and labor performance data across concepts? How should they maximize fraud detection capabilities? How should they arm restaurant operators with the data they need to react to changes affecting day-to-day operations as well as over-time goals?

An industry-leading data model, integrated metadata, and prebuilt reports and dashboards deliver the answers to these questions and more. Deliver relevant, actionable mobile analytics for the restaurant industry with an integrated solution of Oracle Business Intelligence and Oracle Endeca Information Discovery.

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Empower Mobile Restaurant Operations Analytics with Oracle business Intelligence and Endeca

  1. 1. Empower Mobile Restaurant Operations Analytics with Oracle Business Intelligence and Endeca facebook.com/perficient twitter.com/Perficientlinkedin.com/company/perficient
  2. 2. Perficient is a leading information technology consulting firm serving clients throughout North America. We help clients implement business-driven technology solutions that integrate business processes, improve worker productivity, increase customer loyalty and create a more agile enterprise to better respond to new business opportunities. About Perficient
  3. 3. About Patrick Abram Photo Passion: Finding not only the right answers, but also which are the right questions. Skills: Planning and delivery of Oracle CRM and Oracle Business Intelligence solutions. Oracle University instructor. Education: Bachelors of Science in Mathematics from Purdue University Personal notes: • Black belt in Tae Kwon Do • Favorite Quote: “Truth suffers from too much analysis.” – Frank Herbert
  4. 4. Agenda 1. Restaurant Management 101 2. Advanced Analysis 3. Multi-Concept Approach 4. Solution Architecture 5. The Data Warehouse 6. Core Report Examples 7. Why Act Now? 8. Next Steps 6/23/2014
  5. 5. Restaurant Management 101
  6. 6. Restaurant Science – Two Points of View Kitchen Management Food Quality & Costs Gordon Ramsay Kitchen Nightmares 6/23/2014 6 House Management Process & Profitability Jon Taffer Bar Rescue
  7. 7. Kitchen Metrics Food Quality Food Costs Popularity • # of times an item is ordered Remake % • # of times an item is remade / Popularity Comp % • # of times an item is “comped” / Popularity Total Food Cost • Sum of all food costs Food Cost % • Total Food Cost / Total Food Revenue Food Cost per Head • Total Food Cost / # of customers 6/23/2014 7
  8. 8. House Metrics Process Profitability Covers per Man Hour • # of times a table is seated / total hours Labor Cost per Cover • Labor cost / # of times a table is seated Upsell $ per Man Hour • Upsell (after initial order) $ / server hours Gross Profit • Total Sales Revenue – Food & Bev Cost Available Seat Hour • # of seats * length of service (in hours) Revenue per Available Seat Hour • Total Sales Revenue / Available Seat Hours 6/23/2014 8
  9. 9. Restaurant Science – Common Ground Yelling? …no, it’s the People! 6/23/2014 9
  10. 10. Staff & Labor Metrics Staff & Labor Wage Cost % • Wage $ / Total Sales Revenue Labor Hours • # of hours worked Turnover • # of people employed / # of positions Average Length of Employment • # of days worked / # of positions Average Hourly Pay • Wage $ / # of hours worked Each of the metrics above should be role-typed • Kitchen • House 6/23/2014 10
  11. 11. Advanced Analysis
  12. 12. Affinity Analysis – Product Basket Data analysis technique that identifies co-occurrence relationships between items sold on the same transaction. 6/23/2014 Identifying popular item combinations empowers greater cross-selling & upselling. Identifying “mood setting” items empowers staff to make recommendations that increase ticket totals.
  13. 13. Growth-Share Matrix Invented in 1970 by Bruce D. Henderson for Boston Consulting Group 6/23/2014 13 Stars Question Marks Cash Cows Dogs Relative Market Share  High Low  MarketGrowthRate LowHigh Scatter graph ranking items on the basis of their relative market shares and growth rates. • Stars: Menu items generating strong sales which cost a lot to produce. • Question Marks: Menu items gaining popularity which require tweaking or investment to make profitable • Cash Cows: Menu items that are easy to make, low-cost, and are responsible for a larger share of profits. • Dogs: Menu items that don’t sell well, but are also low cost.
  14. 14. Using the Growth-Share Matrix 6/23/2014 14 Stars Question Marks Cash Cows Dogs Relative Market Share  High Low  MarketGrowthRate LowHigh invest divest mature reinvest liquidateleft unattended
  15. 15. Putting Data to Work: Analytic Pathways Scenario Pricing increase on selected items amounting to a weighted average 2.44% based on the current mix. • The increase of 2.44% in Price is offset by a decline of 1.56% in Product Mix. • This results in an increase of 0.88% in the Average Ticket. • A decline of 0.33% in Traffic further reduces Same Store Sales to a net increase of 0.55%. • Having the relationships of leading indicators defined and the information visible enables proactive management. 6/23/2014
  16. 16. Multi-Concept Approach
  17. 17. Data Across Concepts Apples to Apples Apples to Oranges Strong cross-concept correlation Food Cost % • Total Food Cost / Total Food Revenue Covers per Man Hour • # of times a table is seated / total hours Wage Cost % • Wage $ / Total Sales Revenue Weak or no cross-concept correlation Food Cost per Head • Total Food Cost / # of customers Labor Cost per Cover • Labor cost / # of times a table is seated Average Hourly Pay • Wage $ / # of hours worked 6/23/2014 17
  18. 18. Identifying Correlations A tale of two restaurants side-by-side in the suburbs For one, it was the best of times. For one, it was the worst of times. …but why? What do they have in common? • Location & demographics • Age of building and equipment • Technology infrastructure • Marketing support What are the differences? • Management team • Product mix • Labor turnover What is beneath the numbers? • Food waste from poor FIFO rotation? • Tip % outliers from “comp” fraud? 6/23/2014 18
  19. 19. Solution Architecture
  20. 20. Accelerator vs. Application is a project accelerator, not a pre-built application Why can’t retail analytics be pre-packaged? • Multiple disparate data sources that vary by client • Multiple reporting and planning environments supported • Multiple hardware environments supported Challenges • Data inconsistencies (e.g., sales data does not tie out to inventory data) • Educating data consumers • Drilling down to the correct level of detail We do pre-package standard reporting components • Framework and best practice collected from multiple implementations 6/23/2014
  21. 21. Data Integration 6/23/2014
  22. 22. Core and Optional Oracle Modules 6/23/2014
  23. 23. The Data Warehouse
  24. 24. Sales Detail Fact Lowest granularity fact table • Store • Ticket • Table • Seat • Menu Item Dimensions are Concept-specific • Revenue Center • Order Type • Discount • Tender • Void 6/23/2014
  25. 25. Ticket Fact Next granularity level up • Lose Menu Item • Gain Customer Customer dimension derived from credit card transactions • Full Name • Last 4 of credit card number Summarizes Tip, Tax, & Discount • RP_TIP_F • RP_TAX_F • RP_DISCOUNT_F 6/23/2014
  26. 26. Labor Fact Pay summary for all employees • Kitchen • House • Bar Not intended to replace reports generated from the HR system Vital to overall performance metrics comparing daily revenue to daily labor costs 6/23/2014
  27. 27. Purchase Order & Usage Facts Summary of raw item purchases • Need not actually be “raw” • Can optionally link to GL Standard order quantity can be sourced from ERP or historical Summary of raw item usage • Assumes FIFO usage, but this can be adjusted • Can be used to record spoilage 6/23/2014
  28. 28. Cost Facts Ideal vs. Actual usage drives metrics related to waste / scrap • Waste can be identified early • Unexplained waste can be a sign of direct or indirect theft Menu Item costs are vital • Contribution is fundamental to Growth-Share analysis • Void quantity and amounts provide management insights 6/23/2014
  29. 29. Core Report Examples
  30. 30. Market Basket & Sales by Weekday 6/23/2014
  31. 31. Market Basket Prompts 6/23/2014
  32. 32. Market Basket Refined 6/23/2014
  33. 33. Product Mix 6/23/2014
  34. 34. Labor Productivity 6/23/2014
  35. 35. Why Act Now?
  36. 36. Who Is Doing It Now? Darden Restaurants, Inc. is the world’s largest full-service restaurant operator with over 2,100 locations and 200,000 employees 1 1 http://www.darden.com/ and http://en.wikipedia.org/wiki/Darden_Restaurants Darden Restaurant, Inc. example used for illustrative purposes only. No endorsement of or Perficient is implied. All logos © and ® Darden Restaurants, Inc. 6/23/2014
  37. 37. Who Is Doing It Now? On 04/02/2014 “Darden Uses Analytics to Understand Restaurant Customers” was #5 on InformationWeek’s Elite 100: Winning Digital Strategies. 1 CIO Patti Reilly White said, “We can capture when you enter the restaurant and either get seated right away or quoted a wait time. ... Now we can understand the total guest experience within the four walls.” When discussing future plans, CIO White added, “We're still on a multiyear journey to understand our specific guests. We want to be able to see that this guest has come in this many times to this restaurant or this brand -- or to all eight of our brands. All of our initiatives in the analytics space and the digital space are aimed at how to capture and understand information about the specific guest.” 1 http://www.informationweek.com/strategic-cio/executive-insights-and-innovation/informationweek-elite-100-winning-digital-strategies/d/d-id/1127886 6/23/2014
  38. 38. Monitoring Reduces Fraud Washington University in St. Louis published a study “IT monitoring effective in deterring fraud by restaurant employees” on 09/13/2013. 1 Pierce and his team found that after installing the monitoring software, revenue per restaurant increased an average of $2,982 per week, about 7 percent. Restaurants also experienced a 22 percent drop in theft. “Our results suggest a counterintuitive and hopeful pattern in human behavior,” the researchers write. “Employee theft is a remediable problem at the individual employee level. While individual differences in moral preferences may indeed exist, realigning incentives through organizational design can have a powerful effect in reducing corrupt behaviors in a way that benefits both the firm and its workers.” 1 http://www.sciencedaily.com/releases/2013/09/130903123050.htm 6/23/2014
  39. 39. Next Steps
  40. 40. Planned Development Oracle BI Mobile App Designer The use of Oracle BI Mobile App Designer eliminates the need for an App Store download or additional software. The report pages created will run on any HTML5-compliant device. This unlocks to a greater range of restaurant operators regardless of mobile platform. Leverage Upcoming Cloud Service Connectors for Oracle BI • Oracle RightNow Social Monitor Cloud Service – As it stands alone data from Oracle RightNow is highly valuable for customer satisfaction data down to the store level. – As a source for Oracle Endeca Information Discovery the data from Oracle RightNow can aid the divest / invest and product mix selection decisions. • Oracle Eloqua Marketing Cloud Service – Marketing campaign effectiveness as well as actual lift and cannibalization data can help drive decisions on trade spend decisions at all levels. 6/23/2014
  41. 41. 6/23/2014 41