A Practical Guide to Implementing Levels 4 and 5 · 2017. 5. 19. · Pr edict ab le ( st able) wit hin a r ange Spe c ia l C a us e Va r iat ion Assigna ble var i at ion t hat com

Copyright 2005 Northrop Grumman Corporation

A Practical Guideto ImplementingLevels 4 and 5CMMI Technology Conference & User Group14-17 November 2005

Rick Hefner, Ph.D.Northrop Grumman Corporation

Copyright 2005 Northrop Grumman Corporation2

Agenda

� An Overview of Levels 4 and 5� New Behaviors� Benefits – Project, Organizational, Customer� Making the Business Case

� Understanding the CMMI Process Areas� Organizational Process Performance� Quantitative Project Management� Causal Analysis & Resolution� Organizational Innovation & Deployment

� Strategies for Adoption� Lessons Learned� Links to Six Sigma

SM SCAMPI, SCAMPI Lead Appraiser, and SEI are service marks of Carnegie Mellon University.® Capability Maturity Model Integration and CMMI are registered in the U.S. Patent & Trademark Office.


Causal Analysis and ResolutionOrganizational Innovation and Deployment5 Optimizing

4 QuantitativelyManaged

3 Defined

2 Managed

Quantitative Project ManagementOrganizational Process Performance

Requirements DevelopmentTechnical SolutionProduct IntegrationVerificationValidationOrganizational Process FocusOrganizational Process DefinitionOrganizational TrainingRisk ManagementIntegrated Project Management (for IPPD*)Integrated Teaming*Integrated Supplier Management**Decision Analysis and ResolutionOrganizational Environment for Integration*

Requirements ManagementProject PlanningProject Monitoring and ControlSupplier Agreement ManagementMeasurement and AnalysisProcess and Product Quality AssuranceConfiguration Management

1 Performed

Process AreasLevel

Proactivemanagement

PredictiveManagement

Reactive mgmt.(plan, track, and

correct)

Management Styles in the CMMI

Qualitativeimprovement

Quantitativeimprovement

Project Organizational


Exercise –What is Managing by Variation?

� Suppose your project conductedseveral peer reviews of similarcode, and analyzed the results� Mean = 7.8 defects/KSLOC� +3σ = 11.60 defects/KSLOC� -3σ = 4.001 defects/KSLOC

� What would you expectthe next peer review toproduce in terms ofdefects/KSLOC?

� What would you think ifa review resulted in 11defects/KSLOC?

� 3 defects/KSLOC?

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Observation Number

Indi

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I Chart for Defects

Mean=7.8

UCL=11.60

LCL=4.001


Exercise –What is Required to Manage by Variation?

� What is needed to develop thestatistical characterization of aprocess?

� The process has to bestable (predictable)� Process must be

consistently performed� Complex process may

need to be stratified(separated into simplerprocesses)

� There has to be enoughdata points to statisticallycharacterize the process� Processes must occur

frequently within asimilar context (projector organization)

� May need to stratify thedata

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Observation Number

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Mean=7.8

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LCL=4.001


Freq

uen

cy

Hours to Close

10

Process Example: Closing a change request

1 4 7 10 13 16

15

20

5

0

What Is a Data Distribution?

� The data distributiongives a frequency ofoccurrence of eachvalue in a data set

� Once we characterizethe data distribution, wecan predict futurevalues or assign aprobability to anyspecific value

� Data distributions mayrepresent population orprocess data

� When applied toprocess data - assumesstatistical stability

A bell curve isa Normal orGaussianDistribution

Frequencydistributionof hours toclose


The Normal Distribution

0

50

100

150

200

250

300

350

-16 -12 -8 -4 0 4 8 12 16 20

Data Value

Frequency

of O

ccure

nce

� Commonly called a bell curve;formally called a Gaussiandistribution

� Applies to continuous data (e.g.time, weight, distance)

� Characteristic shape:� Mean, mode, and median are

all the same value� Standard deviation is

independent of the mean

� Normal distributions are not alaw, but they are often observedin natural data� Often the distribution of

difference between plan andactual dates or budget versusactual


Characteristics of a Normal Curve

Once we understand whatkind of distribution ourdata comes from, we canpredict future values orassign a probability toany specific point

• Probability x will occur

• Probability a value < x

• Probability a value > x

• Probability a value willoccur between x and y

De

nsi

ty

3210-1-2-3

0.4

0.3

0.2

0.1

0.0

34%34%

14%14%

2%2%

99.7%

95.4%

68.3%

�=meanσ=1 standarddeviation


The Rayleigh Distribution…

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350

0 1 2 3 4 5 6 7 8

Data Value

Frequency

of O

ccure

nce

� A skewed distribution

� Used to model effort or defectdensity in software developmentwhere the abscissa representsdevelopment phase if they areroughly the same duration

� Rayleigh distribution is a specialcase of the Weibull distribution


What Is a Control Chart?

� A time-ordered plot of processdata points with a centerlinebased on the average andcontrol limits that bound theexpected range of variation

� Control charts are one of themost useful quantitative toolsfor understanding variation


What Are the Key Features of a Control Chart?

ID

Def

ects

per

Lin

eof

Code

252321191715131197531

0.10

0.09

0.08

0.07

0.06

_U=0.07825

UCL=0.09633

LCL=0.06017

Tests performed with unequal sample sizes

UpperControl

LimitProcess“Average”

LowerControl

Limit

Timeorderedx-axis

Individualdata points

U Chart of Defect Detected in Requirements Definition


What is Special Cause and Common CauseVariation?

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� Common Cause Variation� Routine variation that comes

from within the process� Caused by the natural variation

in the process� Predictable (stable) within a

range

� Special Cause Variation� Assignable variation that comes

from outside the process� Caused by a unexpected

variation in the process� Unpredictable

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Observation Number

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I Chart for Defects_

1

Mean=7.467

UCL=13.36

LCL=1.578


What Is a Stable Process?

ID

Def

ects

per

Line

ofCo

de

252321191715131197531

0.10

0.09

0.08

0.07

0.06

_U=0.07825

UCL=0.09633

LCL=0.06017

Tests performed with unequal sample sizes

U Chart of Defects Detected in Requirements Definition

All data points withinthe control limits. Nosignals of specialcause variation.


Hearing Voices

� Voice of the process = the natural bounds of processperformance

� Voice of the customer = the goals established for the product andprocess performance

stable process

Capable process = +

product conformance

� Process capability may be determined for the� Organization� Product line� Project� Individual

� Typically, the higher the level of analysis, the greater the variation


What if the Process Isn’t Stable?

� You may be able to explainout of limit points byobserving that they are dueto an variation in theprocess� E.g., peer review held on

Friday afternoon� You can eliminate the

points from the data, ifthey are not part of theprocess you are trying topredict

� You may be able to stratifythe data by an attribute ofthe process or attribute ofthe corresponding workproduct� E.g., different styles of

peer reviews, peerreviews of different typesof work products

0

5

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UCL

_X

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ects

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Component #

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UCL

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Out of limit points

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UCL

_X

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ects

per

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pone

nt

Component #

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1 11 21 31 41 51 61 71

UCL

_X

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pone

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1 11 21 31 41 51 61 71

UCL

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UCL

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Component #


Common Challenges for Engineering

� Data are often discrete ratherthan continuous, e.g., defects

� Observations often are scarce

� Processes are aperiodic

� Size of the the object oftenvaries, e.g., software module

� Data distributions may not benormal


How Do I Address These Challenges?

� Employ control chart types thatspecifically deal with discrete datadistributions, e.g., u-charts and p-charts

� Use control charts that compensatefor widely variable areas ofopportunity

� Transform non-normal continuousdata to normal data beforeconstructing a control chart (BlackBelt topic)

� Cross check control charts withhypothesis tests (later module) wherefew data points exist


Typical Choices in Industry

� Most customers care about:� Delivered defects� Cost and schedule

� So organizations try topredict:� Defects found throughout

the lifecycle� Effectiveness of peer

reviews, testing� Cost achieved/actual

(Cost Performance Index –CPI)

� Schedule achieved/actual(Schedule PerformanceIndex – SPI)

Defect Detection Profile

0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

160.00

180.00

Req'mts Design Code Unit Test Integrate Sys Test Del 90 Days

Phase

Def

ects

/KSL

OC

All ProjectsNew Process

Process performance• Process measures (e.g., effectiveness, efficiency, speed)• Product measures (e.g., quality, defect density).


How Can High Maturity Help?

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1 2

� By measuring both the meanand variation, the project/organization can assess the fullimpact of an “improvement”

� Can focus on reducing thevariation (making the processmore predictable)� Train people on the process� Create procedures/checklists� Strengthen process audits

� Can focus on increasing themean (e.g., increaseeffectiveness, efficiency, etc.)� Train people� Create checklists� Reduce waste and re-work� Replicate best practices from

other projects

� Can do both

processshift


What Can a Level 4 Organization/Project Do?

� Both can:� Determine whether processes are behaving consistently or have stable

trends (i.e., are predictable)� Eliminate special causes of variation� Identify processes that show unusual (e.g., unpredictable) behavior� Identify the implementation of a process which performs best

� The organization can:� Characterize the process performance of the organization’s standard

process� Develop models to predict process performance

� The organization’s projects can:� Use this data to decide how to tailor the organization’s standard process� Statistically manage selected subprocesses to achieve project quality and

process objectives

Would your organization/projects find this valuable?


Level 5

Level 3

What Does Level 5 Add?

Organizational Process Focus� Goals are qualitative (e.g., get

better)� The effects of the improvements

are not estimated or measured

Organizational Innovation &Deployment

� Goals are quantitative (e.g.,reduce variation by X%, reducemean by Y%)

� Incremental improvements� Innovative improvements - cause

a major shift in processcapability

� Potential improvements areanalyzed to estimate costs andimpacts (benefits)

� Improvements are piloted toensure success

� Improvements are measured interms of variation and mean

Causal Analysis

� Both the project andorganization can betterdetermine cause and effectrelationships

� This can be used to focusprocess improvements andpreventive actions

Builds onLevel 4

capabilities


How Does Level 4 & 5 Benefit the Customer?

� The project fixes the source ofdefects to prevent future defects� Causal analysis

� The project benefits fromimprovements found and provenon other projects

� Organizational innovationand deployment

� Problem behaviors arerecognized faster, enablingquicker resolution

� Quantitative projectmanagement

� More accurate estimates� Organizational processperformance

Better Products and Services Produced Faster And CheaperBetter Products and Services Produced Faster And CheaperBetter Products and Services Produced Faster And Cheaper

“How Does How Does High Maturity Benefit the Customer”, R. Hefner,Systems & Software Technology Conference,. 2005


Agenda





The Project Manager’s Dilemma at Level 3

I want to use the organization’sstandard process, but…

… Does it’s performance and qualitymeet my customer’s expectations?

… If not, how should I tailor theprocess?


� Characterize the performance of the organization’s standardprocess statistically

� Develop models to help a project manager determine theperformance they would be likely to get by using the standardorganizational process model, given their project’s characteristics

What Should the Organization Do to Help theProject Manager?

customer andproject

objectives

OrganizationProject

Standard Process Baselines & ModelsHistorical Data

Tailored ProcessProject Results


Organizational Process Performance

SG 1 Establish Performance Baselines and ModelsBaselines and models that characterize theexpected process performance of the organization'sset of standard processes are established andmaintained.

SP 1.1 Select ProcessesSelect the processes or process elements in theorganization's set of standard processes that are tobe included in the organization's processperformance analyses.

SP 1.2 Establish Process Performance MeasuresEstablish and maintain definitions of the measuresthat are to be included in the organization's processperformance analyses.

SP 1.3 Establish Quality and Process-PerformanceObjectivesEstablish and maintain quantitative objectives forquality and process performance for theorganization.

SP 1.4 Establish Process Performance BaselinesEstablish and maintain the organization's processperformance baselines.

SP 1.5 Establish Process Performance ModelsEstablish and maintain the process performancemodels for the organization's set of standardprocesses.

Selected subprocesses, NOT thewhole process

Objectives deal with eliminatingsources of variation, not setting“stretch” goalsThe organization meets thesegoals by modifying the standardprocess, not driving the projects

Baselines characterize the “voice of theprocess”, based on the existinghistorical data

• What is the current mean andvariation?

May need to subgroup the data

Models allow projects to estimatetheir quantitative performance basedon the historical data of otherprojects executing the process


Quantitative Baselines and Models

� From this baseline (and model), what would you predict the nextpeer review to produce in terms of defects/KSLOC?

� What other models could be developed to help predict?

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BU

ILD N

Process Architecture

RequirementsAnalysis

ArchitecturalDesign

DetailedDesign Fabrication Integration &

Test

ProcessTailoring

ProjectPlanning

ProjectTracking

RiskManagement

SupplierManagement

QualityAssurance

ConfigurationManagement

DataManagement

Measurement &Analysis

DecisionAnalysis &Resolution

Integration

Peer R

eview

Systems

Testing

Systems

Validation

Fagan Inspection

Walkthrough

Desk C

heck

Process ElementsAlternative Process Elements


The Project Manager’s Challenge at Level 4

I understand the capabilities of the organization’s standardprocess, but…

… What are the project’s quality and process performanceobjectives?

… How should I tailor the process?

… What project subprocesses doI need to quantitatively manage?


Quantitative Project Management (Goal 1)

SG 1 Quantitatively Manage the ProjectThe project is quantitatively managed usingquality and process-performance objectives.

SP 1.1 Establish the Project’s ObjectivesEstablish and maintain the project’s qualityand process performance objectives.

SP 1.2 Compose the Defined ProcessSelect the subprocesses that compose theproject’s defined process based on historicalstability and capability data.

SP 1.3 Select the Subprocesses that Will BeStatistically ManagedSelect the subprocesses of the project'sdefined process that will be statisticallymanaged.

SP 1.4 Manage Project PerformanceMonitor the project to determine whether theproject’s objectives for quality and processperformance will be satisfied, and identifycorrective action as appropriate.

Quality: defect levels of keywork products or deliverables

Process: productivity, efficiency,effectiveness of the project’sprocesses

Rationale for how the project tailoredthe organization’s standard process,in order to meet their quality &process performance objectives

• E.g., adding procedures to reducevariation

Assumes the standard processincludes subprocesses to select from

Only some subprocesses selected forstatistical management

• Need not be the same as thoseselected by the organization, or otherprojects

Monitoring against the objectivesestablished in SP 1.1


Outer Loop


SP 1.4 Manage Project PerformanceMonitor the project to determine whetherthe project’s objectives for quality andprocess performance will be satisfied, andidentify corrective action as appropriate.

SP 1.3 Select the Subprocesses that WillBe Statistically ManagedSelect the subprocesses of the project'sdefined process that will be statisticallymanaged


Tailoring

RequirementsAnalysis

ArchitecturalDesign

DetailedDesign Fabrication Integration &

Test

ProcessTailoring

ProjectPlanning

ProjectTracking

RiskManagement

SupplierManagement

QualityAssurance


DataManagement

Measurement &Analysis DAR

Integration

Peer R

eview

Systems

Testing

Systems

Validation

Fagan Inspection

Walkthrough

Desk C

heckRequirements

AnalysisArchitectural

DesignDetailedDesign Fabrication Integration &

Test

ProcessTailoring

ProjectPlanning

ProjectTracking

RiskManagement

SupplierManagement

QualityAssurance


DataManagement

Measurement &Analysis DAR

Organization

Project

SP 1.2 Compose the Defined ProcessSelect the subprocesses that compose the

project’s defined process based onhistorical stability and capabilitydata.


Selecting Subprocesses to be Statistically Managed

� Which processes do you need to be stable(predictable) in order to achieve your project’sobjectives?� For these, eliminate special causes, characterize

the process, and predicatively manage

� The time needed to perform this practice is longand often unpredictable� Many processes can not be made predictable

� Example – objectives for delivered defects� Defect detection (peer review, unit testing, system

testing)� Defect insertion (requirement definition,

architecture, design, integration)



Quantitative Project Management (Goal 2)

SG 2 Statistically Manage Subprocess PerformanceThe performance of selected subprocesseswithin the project's defined process isstatistically managed.

SP 2.1 Select Measures and Analytic TechniquesSelect the measures and analytic techniquesto be used in statistically managing theselected subprocesses.

SP 2.2 Apply Statistical Methods to UnderstandVariationEstablish and maintain an understanding ofthe variation of the selected subprocessesusing the selected measures and analytictechniques.

SP 2.3 Monitor Performance of the SelectedSubprocessesMonitor the performance of the selectedsubprocesses to determine their capability tosatisfy their quality and processperformance objectives, and identifycorrective action as necessary.

SP 2.4 Record Statistical Management DataRecord statistical and quality managementdata in the organization’s measurementrepository.

Type of analysis to be performed(e.g., control charts)

Key is understanding variationin the selected subprocesses(e.g., be able to computestandard deviation), NOT justmetrics

Given the stability and variation inthe subprocesses, will we be ableto meet our project-level qualityand process performanceobjectives?

This data is used to help selectsubprocesses in tailoring (SP 1.2)


Inner Loop


SP 1.4 Manage Project PerformanceMonitor the project to determine whetherthe project’s objectives for quality andprocess performance will be satisfied, andidentify corrective action as appropriate.


SP 2.2 Apply Statistical Methods toUnderstand VariationEstablish and maintain an understanding ofthe variation of the selected subprocessesusing the selected measures and analytictechniques.

SP 2.3 Monitor Performance of theSelected SubprocessesMonitor the performance of the selectedsubprocesses to determine their capabilityto satisfy their quality and processperformance objectives, and identifycorrective action as necessary.


Sample Measures for Quantitative Analysis

� Time between failures� Critical resource utilization� Number and severity of defects in the

released product� Number and severity of customer

complaints concerning the pro-videdservice

� Number of defects removed byproduct verification activities(per-haps by type of verification,such as peer reviews and testing)

� Defect escape rates� Number and density of defects by

severity found during the first yearfollowing product delivery or start ofservice

� Cycle time� Amount of rework time� Requirements volatility (i.e., number

of requirements changes per phase)� Ratios of estimated to measured

values of the planning parameters(e.g., size, cost, and schedule)

� Coverage and efficiency of peerreviews (i.e., number/amount ofproducts reviewed compared to total,number of defects found per hour)

� Test coverage and efficiency (i.e.,number/amount of products testedcompared to total, number of defectsfound per hour)

� Effectiveness of training (i.e., percentof planned training completed andtest scores)

� Reliability (i.e., mean time-to-failureusually measured during inte-grationand systems test)

� Percentage of the total defectsinserted or found in the differentphases of the project life cycle

� Percentage of the total effortexpended in the different phases ofthe project life cycle

� Profile of subprocesses understatistical management (i.e., numberplanned to be under statisticalmanagement, number currently beingstatistically managed, and numberthat are statistically stable)

� Number of special causes of variationidentified

Source: Interpreting the CMMI, Margaret Kulpa and Kent Johnson


New Questions at Level 4

� What characteristics of the organizational standardprocess would be useful to understand?

� Which subprocesses would be useful to understand,for predictive purposes?

� Are these subprocesses predictable (stabilizable)?

� What data should the organization collect?

� To what level of detail should the organizationalstandard process go?

� What differences in project subprocesses arepermissible? How do they impact the historical data?


What Does Level 5 Add to the Project/Organization?

� Casual Analysis & Resolution� Identify and analyze causes of defects and other problems� Take specific actions to remove the causes

� The project may take actions to prevent the occurrence of thosetypes of defects and problems in the future

� Most projects use CAR-type methods and tools at Level 4, toidentify and eliminate special cause variations, i.e., to stabilizethe processes

� At Level 5, CAR is used to eliminate common cause variation

effects


Causal Analysis & Resolution

SG 1 Determine Causes of DefectsRoot causes of defects and other problemsare systematically determined.

SP 1.1 Select Defect Data for AnalysisSelect the defects and other problems foranalysis.

SP 1.2 Analyze CausesPerform causal analysis of selected defectsand other problems and propose actions toaddress them.

Can apply to any cause and effectrelationship, not just defectsTypically, projects will establish alist of potential areas in which toapply CAR, and select some fromthat list

Determine cause and effect(e.g., fishbone diagram,brainstorming) and potentialimprovement action listSelect some actions on the listto implement

SG 2 Address Causes of DefectsRoot causes of defects and other problemsare systematically addressed to prevent theirfuture occurrence.

SP 2.1 Implement the Action ProposalsImplement the selected action proposals thatwere developed in causal analysis.

SP 2.2 Evaluate the Effect of ChangesEvaluate the effect of changes on processperformance.

SP 2.3 Record DataRecord causal analysis and resolution datafor use across the project and organization.

Implemented for each selected action• Evidence will provide samples

Measures the effect of thechange

The effect need not be positive


Organizational Innovation and Deployment

SG 1 Select ImprovementsProcess and technologyimprovements that contribute tomeeting quality and process-performance objectives are selected.

SP 1.1 Collect and Analyze ImprovementProposalsCollect and analyze process- andtechnology-improvement proposals.

SP 1.2 Identify and Analyze InnovationsIdentify and analyze innovativeimprovements that could increasethe organization’s quality andprocess performance.

SP 1.3 Pilot ImprovementsPilot process and technologyimprovements to select which onesto implement.

SP 1.4 Select Improvements forDeploymentSelect process- and technology-improvement proposals fordeployment across the organization.

SG 2 Deploy ImprovementsMeasurable improvements to theorganization's processes andtechnologies are continually andsystematically deployed.

SP 2.1 Plan the DeploymentEstablish and maintain the plans fordeploying the selected process andtechnology improvements.

SP 2.2 Manage the DeploymentManage the deployment of theselected process and technologyimprovements.

SP 2.3 Measure Improvement EffectsMeasure the effects of the deployedprocess and technologyimprovements.

The effects should be measuredquantitatively (as opposed toqualitatively in OPF)


Agenda





Achieving Levels 4 and 5 is Less Predictable

� The time it takes to achieveLevels 2 and 3 is driven by theresources available� Learn/implement new project

practices� Create organizational assets -

policies, processes, training,etc.

� Practices are first performed;effectiveness is improved overtime

� The time it takes to achieveLevels 4 and 5 is driven by theability to stabilize processes� Choosing processes that can

be stabilized� Establishing the right metrics

and methods� Collecting enough data� Effectiveness is required to

perform the practices

Causal Analysis and ResolutionOrganizational Innovation and Deployment5 Optimizing

4 QuantitativelyManaged

3 Defined

2 Managed

Quantitative Project ManagementOrganizational Process Performance

Requirements DevelopmentTechnical SolutionProduct IntegrationVerificationValidationOrganizational Process FocusOrganizational Process DefinitionOrganizational TrainingRisk ManagementIntegrated Project Management (for IPPD*)Integrated Teaming*Integrated Supplier Management**Decision Analysis and ResolutionOrganizational Environment for Integration*

Requirements ManagementProject PlanningProject Monitoring and ControlSupplier Agreement ManagementMeasurement and AnalysisProcess and Product Quality AssuranceConfiguration Management

1 Performed

Process AreasLevel


Lessons Learned

Based on 20 Northrop Grumman CMMI Level 5 organizations� Level 3 metrics, measurement processes, and goal setting are generally

inadequate for Levels 4 and 5� Better definitions of the measures� Lower level metrics of lower level subprocesses� Stratifying the data properly

� When operating at Level 3, it is difficult to predict the measurementimprovements needed� Trying to understand and stabilize the key subprocesses will naturally

drive you to the right metrics

� Projects have different quality and process performance needs, andshould select different subprocesses to quantitatively manage� This will also slow adoption, and complicate the organizational baselines

and models

� Six Sigma is an enabler for higher maturity� Focus on data, measurement systems, process improvement� Tying improvements to business goals� Tools and methods support the level 4/5 analysis tasks


What is Six Sigma?

� Six Sigma is a management philosophy based on meetingbusiness objectives by striving for perfection� A disciplined, data-driven methodology for decision making and

process improvement

� Six Sigma consists of several integrated methods:� Process Management� Voice of the Customer� Change Management� Tools for Measuring Variation and Change� Business Metrics

� Leading-edge companies are applying Six Sigma to engineeringwork


Importance of Reducing Variation

� To increase process performance, you have to decrease variation

� Less variation means� Greater predictability in the process� Less waste and rework, which lowers costs� Products and services that perform better and last longer� Happier customers

Defects Defects

Too early Too late

Delivery Time

Reducevariation

Delivery Time

Too early Too late

Spread of variationtoo wide compared

to specifications

Spread of variationnarrow compared to

specifications


A Typical Six Sigma Project in Engineering

� Customers express concern that software defects are causingfrequent failures in the field

� A Six Sigma team is formed to scope the problem, collect data,and determine the root cause

� The team’s analysis of the data determines that poorlyunderstood interface requirements account for 90% of theproblems in the field

� The interface problems are corrected

� The organization’s requirements solicitation process is modifiedto ensure future projects do not encounter similar problems


DMAIC Process Steps

DEFINE Set project goals and objectives

MEASURE Narrow range of potential causes and establishbaseline capability level

ANALYZE Evaluate data/information for trends, patterns, causalrelationships and "root causes“

IMPROVE Develop, implement and evaluate solutions targetedat identified root causes

CONTROL Make sure problem stays fixed and new methods canbe further improved over time


How Six Sigma Helps Level 4-5 Organizations

� Six Sigma provides specificmethods and tools for:� Quantitative process

management of Level 4� Causal Analysis and

Resolution of Level 5

� Six Sigma projects provide amechanism for selecting andimplementing improvements� Addresses Organizational

Innovation and Deployment� Can extend beyond Level 5


References

� “Squeezing Variation for Profit, “ Don Corpron, CMMI Technology Conference and UserGroup, 2005

� “Using a Process Database to Facilitate Transition to Level 4”, Rick Hefner, InternationalConference on Applications of Software Measurement, 2002.

� Purcell, Leitha, “Experiences Using Six Sigma in a SW-CMM® Based Process ImprovementProgram”, American Society for Quality Six Sigma Conference, January 2001.

� Interpreting the CMMI: A Process Improvement Approach, Margaret Kulpa and Kent A.Johnson, Auerbach Publications, 2003

� Card, David, “Sorting Out Six Sigma and the CMM”, IEEE Software, May 2000.

� iSixSigma, http://www.isigsima.com

Documents

A Practical Guide to Implementing Levels 4 and 5 · 2017. 5. 19. · Pr edict ab le ( st able) wit hin a r ange Spe c ia l C a us e Va r iat ion Assigna ble var i at ion t hat com