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Empower Mobile Restaurant Operations Analytics
with Oracle Business Intelligence and Endeca
facebook.com/perficient twitter.com/Perficientlinkedin.com/company/perficient
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
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
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
Restaurant Management 101
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
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
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
Restaurant Science – Common Ground
Yelling?
…no, it’s the People!
6/23/2014 9
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
Advanced Analysis
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.
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.
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
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
Multi-Concept Approach
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
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
Solution Architecture
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
Data Integration
6/23/2014
Core and Optional Oracle Modules
6/23/2014
The Data Warehouse
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
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
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
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
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
Core Report Examples
Market Basket & Sales by Weekday
6/23/2014
Market Basket Prompts
6/23/2014
Market Basket Refined
6/23/2014
Product Mix
6/23/2014
Labor Productivity
6/23/2014
Why Act Now?
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 Š and Ž Darden Restaurants, Inc.
6/23/2014
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
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
Next Steps
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
6/23/2014 41

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Empower Mobile Restaurant Operations Analytics with Oracle business Intelligence and Endeca

  • 1. Empower Mobile Restaurant Operations Analytics with Oracle Business Intelligence and Endeca facebook.com/perficient twitter.com/Perficientlinkedin.com/company/perficient
  • 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. 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. 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
  • 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. 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. 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. Restaurant Science – Common Ground Yelling? …no, it’s the People! 6/23/2014 9
  • 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
  • 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. 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. 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. 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
  • 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. 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
  • 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
  • 22. Core and Optional Oracle Modules 6/23/2014
  • 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. 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. 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. 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. 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
  • 30. Market Basket & Sales by Weekday 6/23/2014
  • 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 Š and ÂŽ Darden Restaurants, Inc. 6/23/2014
  • 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. 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
  • 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