Pareto Analysis - Onlinemeonline.engin.umich.edu/.../Blackbelt/08t-pareto.pdf · 2010-01-09 ·...

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1 Pareto Analysis

Transcript of Pareto Analysis - Onlinemeonline.engin.umich.edu/.../Blackbelt/08t-pareto.pdf · 2010-01-09 ·...

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Pareto Analysis

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Seven Basic Quality Tools

1. Process Mapping / Flow Charts* 2. Check Sheets

3. Pareto Analysis4. Cause & Effect Diagrams5. Histograms6. Scatter Diagrams (XY Graph)7. Control Charts

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Topics

I. Pareto Principle

II. Performing a Pareto AnalysisConstructing a Pareto Chart

III. Pareto: Frequency Vs. Cost Analysis

IV. Pareto Analysis Exercise Using QETools

V. Pareto Drill Down

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I. Pareto Principle

Pareto* Principle provides the foundation for the concept of the “vital few” and a “trivial many”.

Examples:Quality – a small percentage of defect categories (causes) will constitute a high % of the total # defects.Cost – a small percentage of components will constitute a high % of total product cost.Others: Inventory, absenteeism, downtime.

*Note: Wilfredo Pareto – 19th Century Italian economist studying wealth who observed that a large proportion of wealth is owned by a small percentage of the people. Pareto principle was later applied to quality by J.M. Juran.

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80/20 Rule

Pareto principle is sometimes referred to as the 80/20 rule.

In quality, this rule suggests that ~20% of defect categories will account for ~80% of the total number of defects.

“Vital Few – Trivial Many”

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II. Pareto AnalysisRanking of data by importance in descending frequency (highlights most significant concern)

Example: Reasons for Delays in Preparing New Product Bids

Pareto - New Bid Delays

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First, Obtain Frequency Sum Data for Each Category

From check sheet, create a table of categories and occurrences (i.e., frequency).Example: Reasons for Delays in Preparing New Bids

Reasons for Delays FrequencyInsufficient customer specifications 56Internal pricing information not available 18Wait for application review kickoff 5Requirement change by customer 30Quote package filled out incorrectly 45Wait for engineering resources 8Wait for sales processing resources 10Research for similar product pricing 10Unknown test requirements 11Data base search errors 3

Total 196

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Second, Create a Pareto TableSort in Descending Order (by Freq or Relative Freq)Compute Relative and Cumulative Frequencies

Relative Frequency ~ Frequency / Total (56/196=29%)Cumulative Freq % ~ Running total of % (29% + 23% = 52%)

Reasons for Delays Freq Rel Freq, % Cum Freq Cum Rel Freq, %Insufficient customer spec's 56 29% 56 29%Requirement change by cust 45 23% 101 52%Unknown test requirements 30 15% 131 67%Wait for application review 18 9% 149 76%Pricing info not available 11 6% 160 82%Research similar product pricing 10 5% 170 87%Wait for engineering resources 10 5% 180 92%Wait for sales resources 8 4% 188 96%Quote package incorrect 5 3% 193 98%Data base search errors 3 2% 196 100%

Total 196 100%

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Pareto Chart

Left Y-axis – Frequency or Relative FrequencyRight Y-axis – Nothing or cumulative percentage line.

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III. Pareto Analysis: Frequency Versus Cost (or Severity)

Pareto Analysis may be performed using:Frequency of occurrence (expressed as a frequency count or relative frequency %), OrTotal cost, Or Severity, adverse outcome, or avoidability

Note: the most frequently occurring item may not be the most important item to address first.

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Assessing Cost Impact

Suppose a hospice has the following Pareto Frequency Analysis for Medicare denials.

If the cost for an occurrence varies by category, one may weigh the categories by multiplying the frequency by estimated cost per occurrence (e.g., average cost).

Category FrequencyCost per

OccurTotal Cost

Inc supervisory visit 113 362 40906Not recipient 46 536 24656Unsigned election 12 650 7800Non-terminal disease 11 882 9702Unsigned Certification 8 13790 110320Unmet Level of Care 6 31851 191106Unmet Plan of Care 4 1289 5156

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Pareto: Cost Vs. Frequency

Would the priorities be different based on a cost analysis?

TOTAL 389688

Category Total Cost Relative Frequency

Cumulative Frequency

Unmet Level of Care 191103 49.0% 49.0%Unsigned Certification 110313 28.3% 77.3%Inc supervisory visit 40924 10.5% 87.8%Not recipient 24678 6.3% 94.2%Non-terminal disease 9711 2.5% 96.7%Unsigned election 7802 2.0% 98.7%Unmet Plan of Care 5157 1.3% 100.0%

TOTAL 200

Category Frequency Relative Frequency

Cumulative Frequency

Inc supervisory visit 113 56.5% 56.5%Not recipient 46 23.0% 79.5%Unsigned election 12 6.0% 85.5%Non-terminal disease 11 5.5% 91.0%Unsigned Certification 8 4.0% 95.0%Unmet Level of Care 6 3.0% 98.0%Unmet Plan of Care 4 2.0% 100.0%

By denial

By cost ofdenial

Medicare billed forHigher cost thanexpected based on criteria.

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IV. Lecture Exercise: Pareto Analysis for Loan Turndowns

Defect Categories for Loan Turndowns Closing costs too high, selling home, change in marital status, change in job status, not saving enough, lost interest, interest rate is too high, miscellaneous.

Using the data file, pareto.xls create a pareto table of frequency, relative frequency (%), and cumulative frequency, and then a Pareto Chart.

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Exercise: Pareto Analysis

Step 1: Sum by Defect CategoryUsing QE Tools – perform Binary Cross Tabulation to obtain frequency counts for each category for loan check sheet data.

Step 2: Run a Pareto Analysis Using the Sum Data from Step 1, create a paretotable and chart.

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Step 1: Binary Cross Tabulation

Using check sheet data (see sample of data below) for the different loan turndown categories, select:QETools >> Tabulation >> Binary Cross Tabulation

Note: only first 9 rows are shown from file pareto.xls

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Binary Cross Tabulation Example

From binary cross tabulation, QETools automatically creates new data columns for categories and frequency counts in “Datasheet”

Auto Save CategoriesSum to “Datasheet”

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Step 2: Pareto Analysis

Select: QETools >> Graphical Tools >> Pareto

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Pareto Table: Results

TOTAL 132

Category Frequency Relative Frequency

Cumulative Frequency

HighClosingCosts 63 47.7% 47.7%Selling_home 37 28.0% 75.8%Change_marital 16 12.1% 87.9%Change_job 5 3.8% 91.7%Insuff_Saving 4 3.0% 94.7%Lost_interest 3 2.3% 97.0%rate-too-high 3 2.3% 99.2%miscellaneous 1 0.8% 100.0%

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Pareto Chart by Relative Frequency (with Cumulative Frequency Line)

Pareto Chart

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Based on the following chart, what is the most common loan turndown reason?

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V. Pareto Drill Down

If data set includes stratification or grouping variables, one may perform a Pareto Drill Down.

Drill Down ApproachSubset data for a single item (or items) such as high closing costs.Subset data by some value of grouping variables (e.g., Branch=C, or Branch = C and Closing Costs)Here is the loan turndown data stratified by the worst branch (C) and by Loan Officer.

Loan-Off-C Closing-Costs-C

C-1 2

C-2 10

C-3 0

C-4 2

C-5 8

C-6 0

C-7 0

C-8 6

C-9 2

C-10 2

Occurrences by Loan Officer

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Pareto Drill Down by Branch

Decomposition of data.

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Stratify High ClosingCosts by 4 Branches (C Worst)

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Pareto Drill Down by Loan Officer

Decomposition from a system level down.

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Stratify Branch “C”Closing Costsby Loan Officer

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Summary

Pareto Analysis provides a visual tool to highlight most critical issues.

Pareto analysis often involves a drill down to find root causes.

5 Whys? Keep asking why? In the loan turndown example, have we found the root cause yet?

Note: 3 Loan Officers have most closing cost turndowns.

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Pareto Analysis – Define Phase

Pareto Charts also may be used for project scoping using numerical data during the Define phase.

Common usage Pareto Cost Analysis

Example: if the potential scope encompasses several bars on the Pareto chart, the project may be over-scoped.