SIX SIGMA - Sudan University of Science and Technology · Sigma vs. DPMO •1 sigma ... Key Six...

SIX SIGMASIX SIGMA

Assoc. Prof. Dr. Rashid A. SaeedSudan University of Science and Technology (SUST)

[email protected]

• PhD Comm Eng., UPM

• Senior Researcher – Telekom

Malaysia R&D

– RF Network Engineers™

certified, WiMAX Forum

Biodata

2

– Core Network Engineer™

Certification, WiMAX Forum

– 6σ Yellow, Green, and Black

Belt, Motorola University

Dr. Rashid A. Saeed

What is Sigma?

3

What is mu?

4Dr. Rashid A. Saeed

Mean shift during process improvement

What is Six Sigma?

• A philosophy and set of methods companies useto eliminate defects in their products andprocesses

• Seeks to reduce variation in the processes thatlead to product defectslead to product defects

• A standard of performance equal to 3.4 defectsper million outputs (i.e. near perfection).

– Most operations are about 2.8 sigma (100,000defects / million).

– Very good operations are about 4 sigma (3,500defects / million).


Customer Satisfaction

99% Accuracy

Practical Meaning of “99% Good”

• 20,000 lost articles of mail per hour

• Unsafe drinking water almost 15 minutes each day

• 5,000 incorrect surgical operations per week

• 2 short or long landings at most major airports each day

8

• 2 short or long landings at most major airports each day

• 200,000 wrong drug prescriptions each year

• No electricity for almost 7 hours each month

99% Is NOT Good Enough Anymore

Dr. Rashid A. SaeedIs 99% Good ?

6 σ – The Measurement

99.0% = 3.85 σ σ σ σ

99.9996% = 6 σσσσ

9

99.9996% = 6 σσσσ

Is there really a big difference between

99.0% & 99.9996%?

Dr. Rashid A. Saeed

Sigma vs. DPMO

• 1 sigma – 690,000 DPMO – 31%

• 2 sigma – 308,537 DPMO – 69.14%

• 3 sigma – 66807 DPMO – 93.32%

• 4 sigma – 6210 DPMO – 99.38%• 4 sigma – 6210 DPMO – 99.38%

• 5 sigma – 233 DPMO – 99.97%

• 6 sigma – 3.4 DPMO – 99.99%

When is good is good enough?

Process: A series of tasks or activities whereby one thing (the input) is

changed or used to create something else (the output)

Processes Are Everywhere

else (the output)

Process Vs. Customer

DefectsDefects Acceptable

LSL USL

Customer Requirement

Process Performance

Process Performance And Customer Requirement Often Do Not Match


> A universal problem-solving methodology (DMAIC)

> A rigorous performance improvement approach

> A customer-focused, data-driven approach to understanding process variation (VOP) and defect reduction (VOC)

> A performance target of 3.4 defects per million opportunities

Six Sigma

Target ValueProcess

14

Upper SpecLimit

Lower SpecLimit

After

Before

Process Center

VOCVOP

Where VOP meets VOC!!! Where VOP meets VOC!!! Dr. Rashid A. Saeed

Probability of Defects

Process Capability

• Process capability=[desired performance]/[actual

performance]

• To increase a process sigma level, you have to decrease

variation.Probability of Defects

If delivery time is

the customer

specification

Delivery time

Re

du

ce v

aria

tion

Too lateToo early

USL&LSL: Upper

& Lower

Specification

Limit

15

Unpredictable

XXXX

XXXX

XX

XX

XXXX

XXXX

XX XX XXXX

Off-Target

XXXX

XX

XX

XX

XX

XXXX

XX

XXXX

XX

Six Sigma Focuses on the Elimination

of Variation

CenterProcess

ReduceSpreadXX

XXXX

XXXX

XX

XXXX

XXXX

XX XX XXXX

On-Target

XX

XX

XXXX

XX


6 Sigma – The Basic Process

1. Understand the Customer Requirements

2. Reduce Variation Waste Within The Process To Reduce the Defects

17

3. Center the Process Around The Customer Requirements

4. Control The Process

Lean Project Attributes

• Simply stated: “Lean is about moving the Mean.” It focuses on

efficiency.

– Lean reduces average cycle time.

– Lean reduces excess inventory.

– Lean improves average response time.

Improvement

– Lean improves average response time.


Six Sigma Attributes

• Simply stated: “Six Sigma is about Reducing

Variation.” It focuses on Effectiveness. The

mean will most likely also be improved.

– Decrease defect rate

Improvement

– Decrease defect rate

– Increase Process Yield

19

Process Management

helps us maintain

good results as we

perform our

Mission.

Strategic planning helps us

“focus” on key projects to

reach our Vision.

Mission.Process

Improvement using

the DMAIC

process


Key Six Sigma Concepts

• Critical to quality: attributes most important to the customer

• Defect: failing to deliver what customer wants• Process capability: what your process can

deliverdeliver• Variation: what customer sees and feels• Stable operations: ensuring consistent,

predictable processes to improve what the customer sees and feels

• Design for six-sigma: designing to meet customer needs and process capability

Six Sigma Approaches

DMADV – Process Design

DMAIC – Process

Improvement

Six Sigma DMAIC

• DMAIC

– Define the project goals and customer (internal andexternal) deliverables

– Measure the process to determine current performance

– Analyze and determine the root cause(s) of the defects

– Improve the process by eliminating defects

– Control future process performance

• When To Use DMAIC

– The DMAIC methodology, instead of the DMADVmethodology, should be used when a product or process isin existence at your company but is not meeting customerspecification or is not performing adequately.


Six Sigma DMADV• DMADV

– Define the project goals and customer (internal andexternal) deliverables

– Measure and determine customer needs andspecifications

– Analyze the process options to meet the customer needs

– Design (detailed) the process to meet the customer needs– Design (detailed) the process to meet the customer needs

– Verify the design performance and ability to meetcustomer needs

• When To Use DMADV

– A product or process is not in existence at your companyand one needs to be developed

– The existing product or process exists and has beenoptimized (using either DMAIC or not) and still doesn'tmeet the level of customer specification or six sigma level


DMAIC Versus DMADV

• The Similarities of DMAIC and DMADV

– Six Sigma methodologies used to drive defects to less than 3.4

per million opportunities.

– Data intensive solution approaches. Intuition has no place in Six

Sigma -- only cold, hard facts. Sigma -- only cold, hard facts.

– Implemented by Green Belts, Black Belts and Master Black Belts.

– Ways to help meet the business/financial bottom-line numbers.

– Implemented with the support of a champion and process

owner

•Project Selection

•Business Case

•Charter

•SIPOC / VSM

•Process Flows

•Data

•Collection Plan

•Pattern’s In Data

•Process Flows

•Data

•Root Cause Analysis

•Generate Solutions

•Rank & Select

•ROI / Pilot

•Implement

•Control Plan

•Results

DefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControl

DMAIC

26

•SIPOC / VSM

•VOB / VOC

•CTQ Tree

(Six Sigma Problem Solving Model)

•Pattern’s In Data

•Process Capability

•Implement

•E =Q*A

PROBLEM SOLVING MODEL LEAN SIGM A

DEFINE: VOICE OF THE CUSTOMER (VOC) SPECIFY VALUE WHAT ARE YOUR CTQ's?

VOC - REACTIVE OPPOR TUN ITY BUSINESS CASE C HAR TER LEADERSHIP TE AM TEAM SI POC TEAM CTQ 's TEAM

VOC - PROACTIVE PROB LEM STATEM ENT CHAM PION / SPONSOR CHARTER O R VOC PLAN VOC

VOB - BUSINESS OPPORTUNITY STA TEM ENT COACH SIPOC V SM (WHO, WHA T, WHEN, CTQ's

VOB - INTERNAL CUSTOM ER OUTPUT MEASURES TEAM LEADER SUPPLIERS (CURRENT STATE) WHERE AND HOW) E=Q*A

DASHBOARDS SCOPE EXPERIENCE REQUIRED INPUTS REACTIVE VOICE CHAM PION / SPONSOR

BALANCED SCORECA RDS PROJECT PLAN GROUND RULES (TQM ) PROCESS (4-7 STEPS) PROACTIVE VOICE STAKEHOLDER ANA LYSIS

BIG Y's TEAM SELECTION ROLES AND RESPONSIBILITY OUTPUTS AFFINITY BUSINESS CASE / GOA LS

GOA L SETTING PROCEDURE/PROCESS CUSTOMERS KANO MODEL PROJECT PLAN

TIMING COM MITMENT / AVAILABILITY DATA

MEASURE: VOICE OF THE PROCESS (VOP) IDENTIFY THE VALUE STREAM WHAT QUESTIONS ARE YOU TRYING TO ANSWER ?

PRO CESS T IM E

DOOR RED UCTI ON

TEAM BA SELIN E

CTQ" S PER FORM AN CE

OPERATORS

SUBJECT M ATTER / PROCESS EX PERTSVALUE STREAM M AP

FUNCTIONAL DEPLOYMENT CHARTS

SPAGHETTI M APPING

TIME STUDIES / BOTTLENECKS

TEAM DETAI LEDCTQ" S PROC ESSOPERATORS M A PSUBJECT M ATTER / PROCESS EXPERTS

FLIPCHARTS & STICKY NOTESIDENTIFY STEPSIDENTIFY DECISIONS

DENTIFY PROCESS STEP VARIA BLES IDENTIFY PROCESS MEA SURES IDENTIFY PROCESS STEP OUTPUTS

TEAM IPO 's TEAM DA TA TEAM SAM PLIN G TEAM % R&R PG AP GRAP HIC AL VOP - X-BAR, P, SSIPOC WHAT ?'??s COLLEC TIO N DATA TYPE PLAN CLARITY DATA TYPE A NALY S IS VOC - CCR, CTQ'sKANO MODEL DATA TYPE PLAN DATA COLLECTION PLAN REMOVING AMBIGUITY DESCRIPTIVE STATISTICS TYPE OF DATA

CTQ'S CONTINUOUS / DISCRETE -AM OUNT OF VARIATION REPEATABILITY BOX PLOTS TAKT-TIMEWHAT ?'??s LOCATION OF THE DATA -CONFIDENCE REQUIRED REPRODUCIBILITY HISTOGRAMS Cp,Cpk,Pp,PpkWHAT DATA DO Y OU NEED? PROCESS MAPS -PRECISION REQUIRED ACCURACY NORM ALITY (AD) OEE

COLLECTION RESTRAINTS -COST/ TIM E NOISE (SOV) MULTI-VARY CALCULATING SIGM AGAGE R&R CONFIDENCE SAM PLE CALCULATOR BIAS STRATIFICATION SIGM AXL CALCULATOR (WHO, WHAT, WHEN, SIGMAXL DISCRIMINATION SCATTER PLOT SIGM AXL WHERE AND HOW) M INITA B SIGM AXL PARETO MINITAB

MINITAB SIGMAXLM INITA B

ANALYZE: ROOT CAUSE ANALYSIS VALUE ADDED FLOW ANALYSIS DETERMINE ROOT CAUSE / P-VALUES / VA%'s

PR OCES S TI M E

DO OR RE DUCT IO N

TEAM V AFA

SUBJECT M ATTER/PROCESS EXPERTS

CTQ" S V A LUE

TAKT-TIM E AD DED

VALUE STREAM M AP %FUNCTIONAL DEPLOYMENT CHARTS

IDENTIFY

BUSINESS

OPPORTUNITIESCHARTER FORM TEAM SCOPE

PROJECT

VOICE OF THE

CUSTOMER(Y'S TO CTQ'S)

DEVELOP DATA

COLLECTION

PLAN

OPERATIONAL

DEFINITIONS

AND GAGE

R&R

PATTERNS IN

DATA

DETERMINE

PROCESS

CAPABILITY

IDENTIFY I,P,O's

MEASURES

Y=f (X)

(WHAT ?'s)

SAMPLING

PROCESS

OR DATA

DOOR?

DEVELOP

COMMUNICATION

PLAN

DETAILED

PROCESS MAP

(X's)

TIME MAPPINGTIME OR

VARIATION

REDUCTION

D

A

T

A

D

O

O

R

PROCESS

OR DATA

DOOR?

TIME OR

VA RIA TION

REDUCTION

V

A

R

I

A

T

VALUE ADDED

FLOW

ANALYSIS

D

A

T

A

R

E

D

U

C

T

V

A

R

I

A

T

I

O

N

R

E

D

U

C

T

I

O

N

PROCESS

OR DATA

DOOR?

D

A

T

A

D

O

O

R

P

R

O

C

E

S

S

D

O

O

R

Co

un

t

Pe

rce

nt

WasteCount

5.0

Cum % 55.0 80.0 95.0 100.0

55 25 15 5

Percent 55.0 25.0 15.0

InspectingWaitingMovingStoring

100

80

60

40

20

0

100

80

60

40

20

0

Pareto Chart of Waste

Class

Favorite Funny

Six

Sigma Unique SUM

Weight 5 4 3 2

Option

CIAMD 1 3 2 3 29

AKA 3 3 2 3 39

Slackers 4 4 4 3 54

Late 2 3 3 3 37

Month

Ind

ivid

ua

l V

alu

e

Dec-05

Oct-05

Aug-05

Jun-05

Apr-05

Feb-05

Dec-04

Oct-04

Aug-04

Jun-04

Apr-04

Feb-04

100

99

98

97

96

95

94

93

_X=97.210

UB=100

LCL=93.738

Customer Satisfaction ScoreCTQ’s

Dr. Rashid A. SaeedVCM: VALUE CHAIN MANAGEMENT E =Q x A. Effectiveness = Quality x Acceptance

Display Problem ...

WH

AT

WH

ER

E

WH

EN

WH

O

OU

TC

OM

E

Stratify Problem ...

1. Define 2. Measure

3. Analyze 4. Improve

Checksheetor Spreadsheet Line Graph

Month

GOOD

Target

GAP

%

Histogram

n=63

21 Late

n=21

Pareto

B C A D

PROBLEM STATEMENT

Identify & Verify Root Cause ... Identify & Implement Countermeasures ...Countermeasures MatrixSingle Case Bore Contingency Table

FISHBONE

RE

AS

ON

/F

AC

TO

R

1

CASE

2 3 4 5 APresent

EffectCauseProblem

No Problem

35 3

AEFFEC

PROBLEM STATEMENT

ROOT CAUSE

AA1

A2

C1

4 4 16 Y

5 4 20 Y

EF

F

FE

AS

OV

RL

AC

TN

?

3 2 6 NCM

Standard

Results Standardization Future Plans

A

B

C

AAbsent

4 25

Scatter Diagram

Cause "C"

Eff

ec

t

B

CT

CC1

C2

5 4 20 Y

3 1 3 N

BARRIERS AIDS

High A1a A1b

HOW WHO

1. Dev2. Impl

WHEN

CONTROL CHARTS

FLOW CHART

LESSONS LEARNED

WHAT'S NEXT?

GOOD

%

CM IMPL'M

Before After

n=21

n=10

OverallEffect

B C A D C B A D

Target

Action Plan

5. Control4. Improve

27

Sample Primary MetricProduct ReturnsProduct Returns

44%%

55%%

66%%

77%%

Re

turn

$ A

s %

Sa

les

$R

etu

rn $

As

% S

ale

s $

00%%

11%%

22%%

33%%

Au

g-9

9

Se

p-9

9

Oc

t-9

9

No

v-9

9

De

c-9

9

Ja

n-0

0

Fe

b-0

0

Ma

r-0

0

Ap

r-0

0

Ma

y-0

0

Ju

n-0

0

Ju

l-0

0

Au

g-0

0

Se

p-0

0

Oc

t-0

0

No

v-0

0

De

c-0

0

Re

turn

$ A

s %

Sa

les

$R

etu

rn $

As

% S

ale

s $

BaselineBaseline

ActualActual

ObjectiveObjective

28

Six Sigma DMAIC Roadmap

• D - Define Phase:

– Define Customers and Requirements (CTQs)

– Develop Problem Statement, Goals and Benefits

– Identify Champion, Process Owner and Team – Identify Champion, Process Owner and Team

– Define Resources

– Evaluate Key Organizational Support

– Develop Project Plan and Milestones

– Develop High Level Process Map

Define Phase

• D1. Project Charter:– Problem Statement: "Competitors are growing their levels of satisfaction with

support customers, and they are growing their businesses while reducing support costs per call. Our support costs per call have been level or rising over the past 18 months, and our customer satisfaction ratings are at or below average. Unless we stop – or better, reverse this trend – we are likely to see compounded business erosion over the next 18 months."

– Business Case: "Increasing our new business growth from 1 percent to 4 percent (or better) would increase our gross revenues by about $3 million. If we can do this without increasing our support costs per call, we should be able to realize a net gain of at least $2 million."

– Goal Statement: "Increase the call center's industry-measured customer satisfaction rating from its current level (90th percentile = 75 percent) to the target level (90th percentile = 85 percent) by end of the fourth quarter without increasing support costs."

Define Phase

• D2. Customer Requirements

– A SIPOC table (Suppliers, Inputs, Process, Outputs

and Customers) develops a detailed view of all the

important customers, their requirements, and the important customers, their requirements, and the

related process step and supplier dependencies.

– Voice-of-Customer (VOC) Interviews: Group

interview the representative samples of the

company's customers.

– Summarizing Customer Requirements

DEFINE: Story ComponentsTo define the customer, the CTQs, the team charter, and map the core business process

Identify BusinessOpportunity/Gap

Identify Customer’s

• Select measures that link process performance to problem area related to CTQ

• Shows need for improvement

DevelopPreliminary Problem Statement

Select Resources (% Time) and Charter Project Good

Identify Outcome Indicators

Run Chart

32

Identify Customer’s Critical To Quality (CTQ) Attributes

Map High Level Processes and Set Boundaries

Preliminary Problem Statement

Prepare Communication & Project Plans

Who What When

AA BB CC DD EECore

1D

AD

BD

CD

DD

E

AA BB CC DD EE

L D AD

BD

CD

DD

ED AD

BD

CD

DD

E

AAAA

DA

DA

Stakeholder Analysis

Assess Financial $ Impact (COQ)

Project Planning Worksheet

VOB

# Days for return

Return Time

CTQ’sDriversVoice~28 days

Baseline48 hrs

Goal

-1.79 σ 2.78 σ

Time & $/caseResources TBD TBD

Dr. Rashid A. Saeed

The objective of step The objective of step 1 1 is to “Demonstrate the importance is to “Demonstrate the importance

of improvement needs in measurable terms.”of improvement needs in measurable terms.”

DMAIC Overview DMAIC Overview –– Step Step 11: Define: Define

Define Measure Analyze Improve Control33

Step Step 11: Define : Define -- Line Graph ToolLine Graph Tool

• Used to display performance trends

• Relates performance to a target that is established by either customers or the business

• Displays the Gap between the observed performance and the target


Define Phase

• D3. High Level Process

Map:

– The process map will be

helpful during the Measure

phase, as the project team phase, as the project team

considers how and where to

gather data that will shed

light on the root cause of

the issues most pertinent to

the project's goals.


Cause-and-Effect (C&E) MatrixFMEA: Failure Mode, Effect Analysis

Y=ƒ (x1, x2, x3…xn)

Y=ƒ (x1, x2, x3…xn)

2. Measure

1. DefineProblem statement

Baseline

Business Case

Target statement

Stakeholder analysis

Risk analysis

5. Control Validation Control mechanisms Governance

Training

Robustness

Y=ƒ (x1, x2, x3…xn)

2. Measure

3. Analyze

Cause & Effect

Historical or new data?

Measurement System analysis

“As Is” process map

Critical few

Benchmark

Y=ƒ (x1, x2, x3…xn)

4. ImproveCost-benefit analysis

Risk Analysis

Implementation plan


• M - Measure Phase:

– Define Defect, Opportunity, Unit and Metrics

– Detailed Process Map of Appropriate Areas

– Develop Data Collection Plan – Develop Data Collection Plan

– Validate the Measurement System

– Collect the Data

– Begin Developing Y=f(x) Relationship

– Determine Process Capability and Sigma Baseline

Measure Phase

• M1. Refine the Project Y(s)

– During this step the team considered exactly how the project Y(s)

would be defined and measured:

Y(s) Measurement Y(s) Measurement

Primary CustomerSatisfaction

1. By industry standard monthly survey2. The project will require additional, more frequent, case-by-case customer satisfaction data. A measurement system that tracks with the industry survey will be devised and validated.

Secondary Supprt Cost(Per Call)

The staff time connected with each call:- Call answering and discussion- Case research- Callback time

will be loaded with a distribution of benefits and infrastructure costs to compute overall support cost per call.

Measure Phase

• M2. Define Performance Standards for the Y(s)

Measure Current Baseline Target

Primary Customer Satisfaction(Per Collins Industry Assessment)

90th Percentile / 70-80% Satisfied

90th Percentile / 85% Satisfied

Secondary Support Cost Per Call 90th Percentile / $40 90th Percentile / $32

Measure Phase

• M3. Identify Segmentation Factors for Data

Collection Plan

– How is Y naturally segmented

– What factors may be driving the Y(s)? – What factors may be driving the Y(s)?

• Y-to-x tree

• cause-and-effect diagrams

• cause-and-effect matrices

Measure Phase

• M4. Apply Measurement Systems Analysis (MSA)

– Questions Usually Posed for Measurement Systems:

Measure Phase

• M5. Collect the Data: A plan was formulated

to gather data from the past year's database.

• M6. Describe and Display Variation in Current

Performance Performance

– How is the Y Distributed?

– Variation above and below the chart's control

limits suggested that there were "special causes"

in play – worth understanding in more detail by

the team in the Analyze phase.

Measure Phase

• M4. Apply Measurement Systems Analysis (MSA)

– Questions Usually Posed for Measurement Systems:


• A - Analyze Phase:

– Define Performance Objectives

– Identify Value/Non-Value Added Process Steps

– Identify Sources of Variation – Identify Sources of Variation

– Determine Root Cause(s)

– Determine Vital Few x's, Y=f(x) Relationship

Analyze Phase

• A1. Measure Process Capability: Before segmenting the

data and "peeling the onion" to look for root causes and

drivers, the current performance is compared to

standards (established in step M2 of the Measure phase).

• A2. Refine Improvement Goals: If the capability

assessment shows a significant departure from

expectations, some adjustment to the project goals may

need to be considered.

Analyze Phase

• A3: Identify Significant Data Segments and

Patterns:

– By segmenting the Y data based on the factors (x's)

identified during the Measure phase – the team identified during the Measure phase – the team

looks for patterns that shed light on what may be

causing or driving the observed Y variation.

Analyze Phase

• A4: Identify (Refined/More Detailed List of) Possible x's

– Collecting the findings that came out of A3, the team posed strongest in the form of "why" questions:

• Why do Problems and Changes cost more than other call types?

• Why are calls processed on Mondays and Fridays more expensive? expensive?

• Why do transfer rates differ by call type? (higher on Problems and Changes, lower on others)

• Why are wait times higher on Mondays and Fridays and on Week 13 of each quarter?

Analyze Phase

• A5: Identify and Verify

the Critical x's

– To sort out the real drivers

from the "likely suspects"

list built in A4, there is list built in A4, there is

generally a shift from

graphical analysis to

statistical analysis.

– The figure shows that the

influence of callbacks on a

call's wait time

Analyze Phase

• A6: Refine the Financial Benefit Forecast

– Given the "short list" of the real driving x's, the

financial model forecasting "how much

improvement?" may need to be adjusted. improvement?" may need to be adjusted.

Example: Cause-and-Effect Diagram

55


• I - Improve Phase:

– Perform Design of Experiments

– Develop Potential Solutions

– Define Operating Tolerances of Potential System – Define Operating Tolerances of Potential System

– Assess Failure Modes of Potential Solutions

– Validate Potential Improvement by Pilot Studies

– Correct/Re-Evaluate Potential Solution

Improve Phase

• I1. Identify Solution Alternatives to Address Critical x's:

– Consider solution alternatives from the possibilities identified

earlier and decide which ones are worth pursuing further.

Driving Xs (from Analyze phase) Solution Alternatives

Staffing + Add staff Mondays and Fridays, reduce staff on Sundays+ Develop staffing model+ Create on-call list to fill-in for absentees

Web Service Percentage + Focus on services that can be done best on the Web+ Define and communicate the value prop to customers+ Evaluate incentives to move traffic to the Web

Transfers and Callbacks + Improve call center processes to reduce transfers and callbacks

without impacting customer satisfaction

Improve Phase

• I2. Verify the

Relationships Between x's

and Y(s)

– What are the dynamics

connecting the process x's connecting the process x's

with the critical outputs

– Use regression analysis to

verify the relationships

Improve Phase

• I3. Select and Tune the Solution

– Using predicted performance and net value, decide what is the best solution alternative.

– Based on everything the team had learned, it recommended:

• Start with Staffing (the "quick fix"). It is the fastest and surest way to stem the erosion of business growth. ("We recognize it is costly and not highly

• Start with Staffing (the "quick fix"). It is the fastest and surest way to stem the erosion of business growth. ("We recognize it is costly and not highly scalable (to other centers, other languages, etc.). This should be a first step, with the hope that it can be supplanted as the solution elements in other recommendations reduce staff needs.)

• Web Service Percent. Begin right away tracking the call volume and customer satisfaction with this service mode.

• Transfer and Callback reduction. Start right away. This is a "no brainer" net benefit that should work well in parallel with the first two solution elements.

Improve Phase

• I4. Pilot / Implement Solution:

– If possible, pilot the solution to demonstrate results and to verify no unintended side effects.

• Preparation and deployment steps for putting the pilot solution in place.

• Measures in place to track results and to detect unintended side effects.

• Awareness of people issues. • Awareness of people issues.

– Measure and compare the improvement of the solution

Example: Opportunity Flow Diagram

61


• C - Control Phase:

– Define and Validate Monitoring and Control System

– Develop Standards and Procedures

– Implement Statistical Process Control

– Determine Process Capability – Determine Process Capability

– Develop Transfer Plan, Handoff to Process Owner

– Verify Benefits, Cost Savings/Avoidance, Profit Growth

– Close Project, Finalize Documentation

– Communicate to Business, Celebrate

Control Phase

• C1. Develop Control Plan

– The Control plans addressed two views

• Management control: It often focus on the Y(s) or

outcomes of the process and often some of the x's as outcomes of the process and often some of the x's as

well

• Operational control: It concerned with the x's that are

predictive of outcome Y(s).

– Operational control information included both controllable

and "noise" variables

– Operational control information was provided more

frequently than management control information

Control Phase

• C2. Determine Improved Process Capability

– Use the same measures from Define and Measure

in order to provide comparability and monitor

impact in a consistent way. impact in a consistent way.

• C3. Implement Process Control

– Create, modify and use data collection systems

and output reports or dashboards consistent with

the control plan.

Control Phase

• C4. Close Project

– Prepare the implementation plan, transfer control

to operations, conduct project post-mortem, and

archive project results. archive project results.

Example: Control Chart

66

EC5108 67

SIX SIGMA - Sudan University of Science and Technology · Sigma vs. DPMO •1 sigma ... Key Six...

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Transcript of SIX SIGMA - Sudan University of Science and Technology · Sigma vs. DPMO •1 sigma ... Key Six...