the perc methodology improving operations using data mining techniques with a common sense approach...
TRANSCRIPT
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The PERC Methodology
Improving OperationsUsing Data Mining Techniques with a
Common Sense Approach to Doing Business
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The PERC Methodology
Performance Evaluation Report Card (PERC) Methodology
One of the ten finalists in the 2010 WIPRO/Knowledge@WhartonInnovation Tournament
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The PERC MethodologyTypical Application Scenario
• Business or Government Entity with Several Similar Operating Units– General Motors, Ford -- Automotive Dealerships– Health and Human Services – Medicare, Medicaid, etc.– McDonald’s -- Hamburger Franchises – FDIC – Commercial and Savings Banks – Walmart, Target, Retail Stores – Multiple Outlets– Department of Education -- Schools, Guaranty Agencies– Etc. Etc. Etc. . . . Etc. Etc. Etc.
• Large Volume of Data Resources That:– Seem Unmanageable or Incomprehensible– Unwieldy, Making Easy Access to Important Information Difficult– Typically Require Non-Business IT Types to Access– Result in Lost Opportunities From Information Mismanagement
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The PERC MethodologyTypical Application Scenario (continued)
• Opportunities Exist to Improve Operations with Better Information Management and Technology– Improve Productivity
– Move All Units Towards Best Practices
– Gain Competitive Advantage
– Increase Shareholder/Stakeholder Value
– Reduce Costs
– Reduce Risk or Potential Fraudulent Activities
– Increase Awareness of Critical Success Factors Throughout Organization
– Increase Customer/Client Satisfaction
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The PERC MethodologyThrough Improved Data Management
Quantitative AnalysisStatistical Analysis
Expert Systems
Data Source 1 Data Source 2 Data Source 3 Data Source 4
FraudDetection
ExpertSystems
ExecutiveInformation
Systems
ManagementSummary Reports
ForecastingModels
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The PERC MethodologyDrive Toward Best Practices
Time
Per
form
an
ce R
ati
ng
s
Worst
Best
Identifying performance differences drives business
towards best performances. As the poor performers
improve, so does the average or normal business improve.
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The PERC MethodologyThrough Quantitative Business Analysis
Risk ManagementCost Reduction
Growth OpportunityBudget Solution
Policy DevelopmentProfit Increase
Operational Efficiency
NormsVariances
RegressionsCorrelationSampling
AlgorithmsNPV
FinanceOperationsBudgetingMarketingAccounting
Planning
TrendExpert
ModelingGraphics
RatiosDemographics
Quantitative
Business
AnalysisStrategic
ManagementInformation
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The PERC MethodologyThrough Improved Data Management
Quantitative AnalysisStatistical Analysis
Expert Systems
Data Source 1 Data Source 2 Data Source 3 Data Source 4
FraudDetection
ExpertSystems
ExecutiveInformation
Systems
ManagementSummary Reports
ForecastingModels
Changes inPolicy & Operation
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Improving OperationsUsing the PERC Methodology
Approach
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The PERC MethodologyThe Eight-Step Approach
• Step 1: Establish a Strong Business Oriented Focus Group or Executive Dictum
• Step 2: Clearly Define Business Objectives at the Start
– Simplify and Clarify
• Step 3: Identify and Evaluate Available Data Sources for Solving Objectives
– Determine Data Quality -- Comprehensiveness, History, Value & Integrity
– Depending on Findings -- Stop or Move Forward -- If Forward,
• Step 4: Perform Rapid Quantitative Business Analyses
– Identify Relevant Indicators, Establish Benchmarks, Trend History
– KISS -- Keep It Simple Stupid
– Add Complexity Only As Necessary -- Probably Better in Feedback Cycle
• Step 5: Present Findings and Concept for “Smart” System Products
• Step 6: Design & Develop “Smart” System Products for Accomplishing Objectives
• Step 7: Implement, Evaluate, and Obtain Operational Feedback
• Step 8: Refine or Revise and Update Appropriately
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The PERC MethodologyThe Eight-Step Approach
• Step 1: Business Oriented Focus Group Phase
• Step 2: Business Objective Phase
• Step 3: Data Evaluation Phase
• Step 4: Rapid Quantitative Business Analysis Phase
• Step 5: “Smart” System Concept Phase
• Step 6: Design & Development Phase
• Step 7: Implementation Phase
• Step 8: Refine & Update Phase
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The PERC Philosophyto Improving Operations
KEEP IT SIMPLE STUPID
ADD
COMPLEXITY ONLY AS NEEDED
KISS + COAN
If what is done cannot be understood
then the value, itself, is questionable
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The PERC MethodologyStep 1: Establish Business Oriented Focus Group
• Organize a Team of Individuals With:
– A Business Oriented Focus
– Relevant Systems Knowledge
– Operational Knowledge and Experience
• Include Both Line and Staff Level Personnel
– Decision Making Authority
– Enthusiasm for Rapid Development Projects
• Alternatively– CEO Directive
– Executive Dictum
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The PERC MethodologyStep 2: Business Objective Phase
• Clarify the Fundamental Business Objectives – Improve Productivity?
– Reduce Costs?
– Increase Sales & Revenue?
– Increase Shareholder/Stakeholder Value?
– Improve Customer Satisfaction?
– Investigate Fraudulent Activities?
• Keep the Objectives Simple -- But Not Too Narrow (e.g.,– Correct Payments or Cost Savings -- Why not Both?
– Default Risk or Improved Operations -- Why not Both?
– Improved and Timely Management Information
• Identify Data Resources for Benchmarking Objectives– Obtain Access for Analytical Purposes
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The PERC MethodologyStep 3: Data Evaluation Phase
• Evaluate Available Data Sources for Solving Objectives– Determine Data Quality -- Comprehensiveness, History, Value & Integrity– Depending on Findings -- Stop or Move Forward
• Discuss -- How Do We Go About Doing This?– Simply, Logically and Quickly– Entire Population, Sample Population, or Pilot Group– Frequency Distributions of Coded and Date Fields– Identify Potential Outlyers -- Negatives, Min’s, Max’s, Variances, Missing Data– Obtain Sums on Every Numeric Field -- Begin Establishing Controls or Numbers to
Validate -- Eliminate Outlyers If Appropriate– Slice & Dice the Key Numeric Fields by Codes and by Month/Year, Year, Etc.– Create New Variables to Help in Validation Process -- Algebra is o’k– Putting It All Together -- Does It Make Sense? Are Key Variables Available?
Can Benchmarks Be Established for Performance Measurements?
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The PERC MethodologyStep 3: Data Evaluation Phase (Continued)
• Data Quality Evaluation -- What Did You Learn? -- Presentation of Findings
• Graphically Present Findings -- • By Program Meaningful Codes • By Time Intervals (e.g., Month/Year, Year, Week, etc.)• By Logical Peer Groups (size, product type, etc.)• While Seeking New & Creative Perspectives for Evaluation
– Provide Supplemental Detailed Outputs Supporting Findings
• Decision Point -- Stop or Move Forward to Analytical Phase– Provide Recommendation– Decision Should Be Clear
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The PERC MethodologyStep 4: Rapid Quantitative Business Analysis Phase
• Perform Rapid Quantitative Business Analyses
– Determine if Conceptual Control Groups Exist
• Establish Best Practice Groups -- Poor Performing Groups
• If Unable, Then Establish Common Sense Business Practices as Initial Measuring Tools (e.g., net income, sales/employee)
– Begin Developing Set of Potential Performance Indicators
– Segregate Data by Peer Groups and/or Other Logical Criteria
– Evaluate Effectiveness of Individual Indicators using Statistical Correlations by Peer Group
• Determine Norms, Variances and Outlyers for Performance Indicators
• Determine Indicators’ Ability to Be Applied Comprehensively
• Consider Amount of Bias in Indicator (May Require Feedback)
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The PERC MethodologyStep 4: Rapid Quantitative Business Analysis Phase (Continued)
• Perform Rapid Quantitative Business Analyses (Continued)
– Seek Monitoring Solution with Multiple Indicators
– Mix and Match Indicators with Different Weighting Schemes to Look for Best Monitoring Mechanism
– Consider Different Rating Evaluation Methodologies• A, B, C, D, F
• 1st Quartile, 2nd Quartile, . . .
• Relationship to an Expected Norm for the Population
• Simple Ranking per Peer Group (e.g., 21st out of 212)
• Ten Point / Hundred Point Scale
– Begin Formulating Concept For “Smart” System Design
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The PERC MethodologyStep 5: “Smart” System Concept Phase
• Determine How This New Knowledge Should Be Implemented– Alternative Media Options
• Database -- LAN, Web-based Intranet, Software
• Report Card -- Hardcopy
– Periodicity of Rating Evaluation
– Forcefully or Experimentally
– Peer Group or Entire Population
– Relative Measurement or Absolute Measurement
• Develop Alternative “Smart” System Concepts, Providing– Pros and Cons
– Recommendation
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The PERC MethodologyStep 6: Design & Development Phase
• Design Output Formats Appropriate For Chosen Media
– Group Information Logically
– Provide User-Friendly Textual and Numeric Displays
• Good, Average, Poor --- High, Medium, Low --- A, B, C
• Color Code Numerics -- Percentiles, Standard Deviations -- Factor Above/Below Norm
– Present Rating Mechanism or Evaluation Clearly
– Provide Information Regarding Peer Group Benchmark Norms
– Show Trend -- Emphasizing Improvements– Seek Self-Improvement Through Fairness
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The PERC MethodologyStep 6: Design & Development Phase (Continued)
• Develop Design
– Program Design Layouts
– Program Rating or Monitoring Mechanism
– Test Program Logic
– Document Program Logic and Production Update Process
– Develop User Documentation / Operating Manuals, Explaining• Business Objectives
• Performance Measurements
• Rating Mechanisms or Methodology
• All Relevant Output Variables
• Feedback Mechanism for Improvement Considerations
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The PERC MethodologyStep 7: Implementation Phase
• Implement System– Install System Pilot or Full Comprehensive Implementation
– Provide User Training• Explain Objectives
• Key Operating Features
• Stress Importance of User Feedback
– Provide Users with Operating Manuals and Contacts for Feedback
– Over Time -- Monitor Benchmarks for Improving Operations
– Focus Group -- Seek Feedback for Improving System
– Evaluate Usefulness and Value of Making System Enhancements
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The PERC MethodologyStep 8: Revise and Update Phase
• Update System
– Update System Based upon Logical Processing Periodicty
– Ensure Update Receives Quality Control
– Identify Major Changes between Previous Period and New Update
– Keep Trend Information
• Revise System– If Feedback Points to Cost-Effective Improvements--Revise
– Can Help Ensure User Acceptance
– Can Reduce Earlier Unforeseen Biases
– Revisions Should Be Somewhat Minor and Quick to Implement
– Remember, Add Complexity Only as Necessary -- KISS
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Improving OperationsUsing the PERC Methodology
Analyze Performance
Standards
Analyze Performance
Standards
Analyze Performance
Standards
Drive Towards Best Practices
Focus on Poor Performers
Evaluate Success and Refine Approach
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Improving Operations thru PERCDrive Toward Best Practices
Time
Per
form
an
ce R
ati
ng
s
Worst
Best
Placing pressure on poor performers drives them
towards best practices. As the poor performers improve, so does the industry average.
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The PERC MethodologyTypical Project – “Fast Track” Implementation
• Focus Group Phase -- (0 weeks) --Done Prior to Project Start
• Business Objective Phase -- (1-2 Days)
• Data Evaluation Phase -- (2-4 weeks) -- Starts Upon Receipt of Data
• Rapid Analysis Phase -- (3-4 weeks) -- Can Start During Previous
• “Smart” Concept Design Phase -- (2-3 weeks)
• Development Phase -- (3-6 weeks) -- Depends on Design Complexity
• Implementation Phase -- (2-4 weeks)
• Refine and Update -- (1-2 weeks) -- Updates Dependent on Periodicity
Typical Project: Fast Track Implementation Requires 3-6 Months