Download - Six sigma - yellow belt program v3-030610

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Congratulations…….. On Joining the Six Sigma Journey

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• What is Quality?

• Know Six Sigma

• Introduction to Six Sigma as methodology

• Awareness with respect to origin and history of Six Sigma.

• The Six Sigma organization

• Variation and Normal Distribution

• The Pareto Principle reading and Making Paretos.

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What is Quality?

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Historically

Proactive Quality“Create process that will produce less or no defects”

Contemporary

Reactive QualityQuality Checks (QC) - Taking the defectives out of what is produced

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ToolsOrganization

Methodology

Process variation

LSL USL

Upper/Lower specification

limits Regression•••••••• •••• •••

••••

•••• •• ••

••• ••••

••••• ••

•••••

Driven by

customer

needs

Enabled by quality team.

Led by Senior Mgmt

Define Measure

Analyze Improve ControlVendorVendorProcess BProcess BProcess AProcess ACustomerCustomer VendorVendorProcess BProcess BProcess AProcess ACustomerCustomer

VendorVendorProcess BProcess BProcess AProcess ACustomerCustomer VendorVendorProcess BProcess BProcess AProcess ACustomerCustomer

Process Map Analysis

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Frequency Cumulative Frequency

Pareto Chart

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Methodologies Standards Capability Models

•Six Sigma•Lean

•ISO 9000, ISO 14000 etc.•COPC•Malcolm Baldrige

•eSCM•CMM•CMMI

Scientific way to improve capability?

Sharing Benchmarked

practices- “Standardizing”

Best practices to build

capability

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• It is a methodology for continuous improvement

• It is a methodology for creating products/ processes that perform at high standards

• It is a set of statistical and other quality tools arranged in unique way

• It is a way of knowing where you are and where you could be!

• It is a Quality Philosophy and a management technique

Six Sigma is not:

• A standard

• A certification

• Another metric like percentage

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• The term “sigma” is used to designate the distribution or spread about the mean (average) of any process or procedure.

• For a process, the sigma capability (z-value) is a metric that indicates how well that process is performing. The higher the sigma capability, the better. Sigma capability measures the capability of the process to produce defect-free outputs. A defect is anything that results in customer dissatisfaction.

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4 Sigma 6,210 Defects



5 Sigma 233 Defects

6 Sigma 3.4 Defects

Sigma levels and Defects per million

opportunities (DPMO)

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Is 99% (3.8) good enough? 99.99966% Good – At 6

20,000 lost mails per hour 7 lost mails per hour

Unsafe drinking water almost 15 minutes each day

One minute of unsafe drinking water every seven months

5,000 incorrect surgical operations per week

1.7 incorrect surgical operations per week

2 short or long landings at most major airports daily

One short or long landing at major airports every five years

200,000 wrong drug prescriptions each year

68 wrong drug prescriptions each year

Example quoted from GE Book of Knowledge - copyright GE

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• The term “Six Sigma” was coined by Bill Smith, an engineer with Motorola

• Late 1970s - Motorola started experimenting with problem solving through statistical analysis

• 1987 - Motorola officially launched it’s Six Sigma program

MotorolaMotorola The company that invented Six SigmaThe company that invented Six Sigma

MotorolaMotorola The company that invented Six SigmaThe company that invented Six Sigma

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• Jack Welch launched Six Sigma at GE in Jan,1996

• 1998/99 - Green Belt exam certification became the criteria for management promotions

• 2002/03 - Green Belt certification became the criteria for promotion to management roles

GEGEThe company that perfected Six SigmaThe company that perfected Six Sigma

GEGEThe company that perfected Six SigmaThe company that perfected Six Sigma

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http://en.wikipedia.org/wiki/List_of_Six_Sigma_companies

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And Now…

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Six Sigma OrganizationSix Sigma OrganizationSix Sigma OrganizationSix Sigma Organization

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Master Black BeltMaster Black Belt

Black BeltBlack Belt Black BeltBlack Belt

Green BeltGreen Belt



- Thought Leadership- Expert on Six Sigma- Mentor Green and Black Belts

- Thought Leadership- Expert on Six Sigma- Mentor Green and Black Belts

- Backbone of Six Sigma Org- Mentor Green Belts- Full time resource- Deployed to complex or “high

risk” projects

- Backbone of Six Sigma Org- Mentor Green Belts- Full time resource- Deployed to complex or “high

risk” projects

- Part time or full time resource- Deployed to less complex projects in areas of functional expertise

- Part time or full time resource- Deployed to less complex projects in areas of functional expertise

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• Basic - Six Sigma Awareness• Green Belt Projects• Participate in Black Belt Projects• Assist business functions with day to day

activities

• Mentor/Train Green Belts• Black Belt Projects• Change Agents• Work along with the business owners

• Mentor/ Train Black Belts• Run Strategic projects• More Strategic than tactical role

Green Belt (GB)Green Belt (GB)

Black Belt (BB)Black Belt (BB)

Master Black Belt (MBB)Master Black Belt (MBB)

Highly paid!Highly paid!Work like a Consultant!Work like a Consultant!

Huge demand in the industry!Huge demand in the industry!

Overall…A high flying Career!!Overall…A high flying Career!!

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BPMSBPMSBusiness Process Management SystemBusiness Process Management System

BPMSBPMSBusiness Process Management SystemBusiness Process Management System

DMAICDMAICSix Sigma Improvement MethodologySix Sigma Improvement Methodology


DMADVDMADVCreating new process which will perform @ Six Creating new process which will perform @ Six

SigmaSigma

DMADVDMADVCreating new process which will perform @ Six Creating new process which will perform @ Six

SigmaSigma

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THE DMAIC MODEL – For attaining Excellence in existing Processes

DefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControl

Combination of change management & statistical analysis

DefineDefine MeasureMeasure AnalyzeAnalyze DesignDesign VerifyVerify

THE DMADV MODEL - Setting up New Processes to Deliver @ SIX SIGMA also known as DFSS ( Design For Six Sigma)

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Define Process Mission Map Process VOC and VOP Build PMS Develop DashboardsIdentify Improvement

Opportunities

Define purpose of the process, its goal and its boundaries

Identify Critical to Quality and Critical to process

Visual representation of performance

Map process steps, identify input/ output measures

MSA, DCP, indicators and monitors

Service excellence and process excellence

The DMAIC cycle

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• To understand the process; it’s mission, flow and scope

• To know the customers and their expectations

• To identify, monitor and improve correct performance measures for the process

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• A logical and structured approach to problem solving and process improvement

• An iterative process (continuous improvement)

• A quality tool with focus on change management

Essentially Six Sigma DMAIC Is……………

Y = F(X1,X2,X3…………………Xn)

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Practical Problem

StatisticalProblem

Statistical Solution

Practical Solution

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DDefine

MMeasure

AAnalyze

IImprove

CControl

Identify and state the practical problem

Validate the practical problem by collecting data

Convert the practical problem to a statistical one, define statistical goal and identify potential statistical solution

Confirm and test the statistical solution

Convert the statistical solution to a practical solution

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Monitor and Sustain implemented solutions / processes and make new processes a way of Life.

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If the outcome of a process when observed over multiple instances / data points is not consistent then the process is termed as a process with variation.

The term variation refers to the amount of fluctuations which creep into a process over time.

Variation doesn’t essentially mean missing targets or customer expectations all the time. Its more about measuring the inconsistency in a process and is a vital measure in determining the process capability.

Variation = Spread around the centre

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Measurement Variation

Generally a result of an improper or non-calibrated measurement system which produces different outputs in different attempts even with all measuring parameters constant.

or

Variation in the way you measure a process

Process Variation

Result of random or non random causes

or

Variation as part of a process

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Measurement system variation is often a result of the following few reasons

1. Inappropriate measurement tools being used providing inaccurate or inconsistent results for the same exercise.

2. Least count is not granular enough to provide precise outputs.

3. Operators not adequately trained etc.

Measurement errors are commonly termed as GRR errors i.e. Gauge of Repeatability and Reproducibility errors

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Common Causes:– Random variation (usual)– No pattern– Inherent in process– Adjusting the process decreases its variation

Special Causes– Non-random variation (unusual)– May exhibit a pattern– Assignable, explainable, controllable– Adjusting the process decreases its variation

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A normal distribution is bell-shaped and symmetric.

The mean (mu) controls the center and standard deviation/variation (s) controls the spread

The distribution is determined by the mean (mu, and the standard deviation (s)

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For any normal curve :

– 68 percent of the observations fall within one standard deviation of the mean.

– 95 percent of observation fall within 2 standard deviations and

– 99.7 percent of observations fall within 3 standard deviations of the mean.

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Add up about 30 of most things and you start to be “normal”

Normal distributions are divide upinto 3 standard deviations on each side of the mean

Once your that, youknow a lot about what is going on

And that is what a standard deviation is good for

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The world tends to be bell-shaped

Most outcomes occur in the

middle

Fewer in the “tails”

(lower)

Fewer in the “tails” (upper)

Even very rare outcomes are

possible(probability > 0)

Even very rare outcomes are

possible(probability > 0)

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11 22 33 44 55 66 77 88 99 1010Sample numberSample number

UpperUppercontrolcontrol

limitlimit

ProcessProcessaverageaverage

LowerLowercontrolcontrol

limitlimit

Out of controlOut of control

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Shot a rifle? Played darts? Shot a round of golf? Played basketball?

Emmett

Jake

Who is the better shot?

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What do you measure in your process? Why do those measures matter? Are those measures consistently the same? Why not?

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Deviation = distance between observations and the mean (or average) Emmett

Jake

Observations

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9

8

8

7

averages 8.4

Deviations

10 - 8.4 = 1.6

9 – 8.4 = 0.6

8 – 8.4 = -0.4

8 – 8.4 = -0.4

7 – 8.4 = -1.4

0.0

871089

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Deviation = distance between observations and the mean (or average) Emmett

Jake

Observations

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7

7

6

6

averages 6.6

Deviations

7 – 6.6 = 0.4

7 – 6.6 = 0.4

7 – 6.6 = 0.4

6 – 6.6 = -0.6

6 – 6.6 = -0.6

0.0

76776

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Variance = average distance between observations and the mean squared Emmett

Jake

Observations

10

9

8

8

7

averages 8.4

Deviations

10 - 8.4 = 1.6

9 – 8.4 = 0.6

8 – 8.4 = -0.4

8 – 8.4 = -0.4

7 – 8.4 = -1.4

0.0

871089

Squared Deviations

2.56

0.36

0.16

0.16

1.96

1.0 Variance

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Jake

Observations

7

7

7

6

6

averages

Deviations Squared Deviations 76776

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Jake

Observations

7

7

7

6

6

averages 6.6

Deviations

7 - 6.6 = 0.4

7 - 6.6 = 0.4

7 - 6.6 = 0.4

6 – 6.6 = -0.6

6 – 6.6 = -0.6

0.0

Squared Deviations

0.16

0.16

0.16

0.36

0.36

0.24

76776

Variance

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Standard deviation = square root of variance

Emmett

Jake

Variance Standard Deviation

Emmett 1.0 1.0

Jake 0.24 0.4898979

But what good is a standard deviation

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Add up the dots on the dice

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Sum of dots

Pro

ba

bili

ty 1 die

2 dice

3 dice

Here is why: Even outcomes that are equally likely (like dice), when you add them up, become bell shaped

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This is also known as the "80/20 Rule“

The rule states that about 80% of the situations of the problem can be traced to 20% of possible causes.

The Pareto principle was developed by an Italian economist who noticed that 80% of the wealth was owned by 20% of the population.

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The Pareto principle implies that we can frequently solve a problem by identifying and attacking the “vital few” sources.

This principle can be applied to most systems and processes.

The concept is used to dissect a large problem into smaller pieces and in order to identify the biggest contributors.

Pareto analysis helps to ‘localize’ the problem

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Most of the equipment breakdowns are due to a small percentage of the equipment.

The majority of calls to a IT help desk are attributed to a small number of reasons.

Most of the errors in any process occur in one or two process steps.

Only a handful of students in the school district account for most of the tardy events.

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A graphical representation of the Pareto Principle.

A series of bars whose heights reflect the frequency of the problem.

A graph where data is categorized to expose patterns.

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Billing relatedPatient

responsibilityCoding related Front end

Patient demo related

Provider credentialing

relatedNot a denial Others

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100MDe Denial Analysis Jan10-Apr10

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Bar height shows relative importance; indescending order

Bars represent each stratified category

Vertical axis shows relative percentages

“Other” category can be used. It’s always last.

Vertical axis shows count of data points

The line shows cumulative percentages

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The Pareto Principle applies if one or more categories account for a large percentage of the occurrences.

Look for the bars that are much taller than the rest.

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Focus your improvement efforts on the largest category or categories of the Pareto Chart, in order to achieve the maximum gain.

Only focus on a smaller bar if it has a larger impact or is easier to fix.

Using only the data from the large categories of the Pareto Chart, determine if they can be further stratified into additional categories.

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Tardiness by Grade

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5th grade 4th grade 3rd grade 2nd grade 1st grade

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2nd level Pareto Chart

If the data from the Pareto chart

can be stratified further, create 2nd or

even 3rd level charts.

Analyze these charts to determine if the

Pareto Principle applies.

When you’ve narrowed down the

problems on the deepest levels you will

start finding root causes.

1st level Pareto Chart Tardiness events by school

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Brentwood Forest Hills Cravensroft Glendale Wendell Smith Maple Street Randall

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3rd level Pareto Chart

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The Pareto Principle does not apply if all the categories account for an approximately equal percentage of the occurrences.

All the bars are about the same height.

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Do not analyze the tallest bar any further. It is clear that this categorization is not related to the root cause of the problem.

You need to find another way to look at the data. - Determine if there is another way to stratify the data.

- Normalize the data (make all the categories comparable by making the thing you are measuring into a rate).

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Occurrences in the “other” category should be redistributed to existing categories or a new category should be created

If you create an “other” category ensure that it is not one of the larger bars on the chart.

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What is a Pareto Chart? A graphical representation of the Pareto Principle.

A series of bars whose heights reflect the frequency of the problem.

A graph where data is categorized to expose patterns.






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Bar height shows relative importance; in descending order

Bars represent each stratified category

Vertical axis (secondary) shows cumulative percentages

“Other” category can be used. It’s always last.

Vertical axis (primary) shows count of data points (Denial Count)

This line shows cumulative percentages

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1. Enter all Attributes that Contribute to the Problem2. Sort occurrences of each one of them in descending order3. Calculate their individual contribution percentage to the overall problem.4. Calculate cumulative frequency to club top contributors together.5. A table Similar to the picture below should appear on your screen.

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Step 2: Go to INSERT tab of excel 2007 and click on COLUMN

Select the 1st histogram of 2D COLUMN

Now the Histogram is ready

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Step 3: Right click on the RED bar, then click on the “Change Series Chart Type”

Then select first Line graph

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Steps for Making Pareto in Excel 2007Step 4:

Right click on the RED line, then click on the “Format Data Series”

Select Series Options

Select Secondary Axis

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Steps for Making Pareto in Excel 2007Step 5:

Right click on the BLUE bar, then click on the “Format Data Series”

Reduce the Gap Width to 0%

Right Click on the secondary Axis> Go to Format Axis> Axis Options

Make the Maximum fixed 100.00

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Steps for Making Pareto in Excel 2007

Step 6: Pareto is Ready for ANALYSIS






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If the data from the Pareto chart

can be stratified further, create 2nd or

even 3rd level charts.

Analyze these charts to determine if the

Pareto Principle applies.

When you’ve narrowed down the

problems on the deepest levels you will

start finding root causes.

Lower Level Pareto Charts






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Covered By

Another Payer

Untimely Filing

Claim Not On File

Claim In Process

Need Notes/Re

ports

Claim Send For

Reprocess

Need Primary

Eob

Allowed Amont Already

Paid

Claim Paid To Patient

Claim Previously Processed

Others

Denial Count 16303 11371 9507 6714 5669 3230 3121 2706 1902 1667 3494

Cumulative Percent 25 42 57 67 75 80 85 89 92 95 100

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100Billing Related Denial Analysis Jan10-Apr10

LMC NJU HNH HH UPGWCMC

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Denial Count 299 268 204 107 774 670 533 391 389 388 379 349 328 317 309 290 263 256 228 218 210 192 190 172 169 164 151 145 137 135 132 120 251

Cumulative Percent 15 29 40 46 50 53 56 58 60 62 64 66 67 69 71 72 73 75 76 77 78 79 80 81 82 83 83 84 85 86 86 87 100

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1st level Pareto Chart

2nd level Pareto Chart

3rd level Pareto Chart

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Download - Six sigma - yellow belt program v3-030610

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