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CMMI and Six Sigma. SC-SPIN February 28,2008. Presentation Outline. Introductory Comments Characteristics of High Maturity Organizations CMMI and Value Streams Measuring Six Sigma. Capability Maturity Modeling Integration (CMMI). Develop/Document Process Refine Process

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cmmi and six sigma

CMMI and Six Sigma

SC-SPIN

February 28,2008

presentation outline
Presentation Outline
  • Introductory Comments
  • Characteristics of High Maturity Organizations
  • CMMI and Value Streams
  • Measuring
  • Six Sigma
capability maturity modeling integration cmmi
Capability Maturity Modeling Integration (CMMI)
  • Develop/Document Process
  • Refine Process
  • LSS is a tool to assist w/ process refinement
  • Standardize process across multiple areas
  • Measure the process
  • Modify based on measurement analysis
characteristics of high maturity organizations
Characteristics of High Maturity Organizations
  • A mature ML 4-5 organization can accurately, quantitatively estimate quality and process performance, make confident commitments to those predictions, and execute those commitments as planned.
  • Statistical and other quantitative methods are used, at both the organizational and project levels, to understand the past, control the present, and predict future quality and process performance.
  • Organizations establish quantitative objectives for quality and process performance based on their business objectives.
  • Individual projects establish their objectives based on those of the organization and the needs of their customers and end users.
characteristics of high maturity organizations1
Characteristics of High Maturity Organizations
  • Projects and individuals use statistical and other quantitative methods to plan, monitor, take corrective actions, and predict progress against their objectives.
  • Key subprocesses are identified and statistically managed.
  • The performance of key subprocesses is known and used to compose a overall processes to meet organizational and project objectives.
  • High Maturity capabilities allow organizations to:
    • Use information from individual projects to understand and refine project performance and variation for the organization’s standard processes
    • Know what their process limitations are so they do not over commit
    • Target areas for continuing improvement
    • Evaluate quantitatively the impact of proposed improvements.
characteristics of high maturity organizations2
Characteristics of High Maturity Organizations
  • Prerequisites for a High Maturity organization:
    • The ability to gather and use meaningful data at all levels from individual practitioners to projects to the organization itself
    • Defined processes for projects that specify how and when data are collected for use in quantitatively managing the projects
    • Consistent tailoring of the project’s defined processes from the organization’s standard processes
    • A functioning Measurement and Analysis (MA) process area that collects data at the practitioner and project levels and elevates that data to the Organizational Measurement Repository for use by other projects
    • An understanding of what constitutes meaningful and useful measurement data
    • An understanding of the types of variation that are present in all processes
cmmi maturity level 4 process areas
CMMI Maturity Level 4 Process Areas
  • Organizational Process Performance (OPP)
    • The purpose of Organizational Process Performance (OPP) is to establish and maintain a quantitative understanding of the performance of the organization’s set of standard processes in support of quality and process-performance objectives, and to provide the process-performance data, baselines, and models to quantitatively manage the organization’s projects.
  • Quantitative Project Management (QPM)
    • The purpose of Quantitative Project Management (QPM) is to quantitatively manage the project’s defined process to achieve the project’s established quality and process-performance objectives.
  • OPP and QPM are very tightly coupled and require very close cooperation between the organization and the projects to realize their benefits.
cmmi maturity level 4 process areas1
CMMI Maturity Level 4 Process Areas
  • Comments on Organizational Process Performance (OPP):
    • The organization builds a set of Common Measures (in the Organizational Measurement Repository) that represents actual performance of processes for individual projects. These Common Measures are statistically analyzed as to distribution and range and then applied to any individual project in the organization.
    • Quantitative objectives for quality and process performance are established for the organization and are based on the organization’s business objectives and the actual past performance of projects.
    • Performance Baselines and Models are established for the organization’s set of standard processes (OSSP):
      • Process Performance Baselines = Measurements of actual performance for the OSSP. Include a distribution of results that can be used by all projects for estimation purposes.
      • Process Performance Models = Predictors of future performance of the OSSP and of processes in a project’s lifecycle – may use simulations and other statistical methods
    • A quantitative understanding of the OSSP enables individual projects to know how to compose/tailor their defined processes so that their objectives are realistic and can be met.
cmmi maturity level 4 process areas2
CMMI Maturity Level 4 Process Areas
  • Quantitative Project Management (QPM) involves the following:
    • Establishing and maintaining the project’s quality and process-performance objectives
    • Identifying suitable subprocesses from the OSSP baselines and models to tailor and include at the project level
    • Selecting the project subprocesses that should be statistically managed and monitoring their performance
    • Sending appropriate statistical and quantitative data to the Organizational Measurement Repository
    • Understanding the nature and extent of the variation experienced in the project’s process performance
    • Determining if the project’s quantitative objectives for quality and process-performance can be met
    • Ensuring that there is not a misalignment between the Voice of the Customer [Specification Limits] and the Voice of the Process [Control Limits] -- desired results vs. capability
  • The principles of QPM can be applied to projects, support groups, and functional areas
quality management system qms involving value streams
Quality Management System (QMS) Involving Value Streams
  • QMS methodology must support the initiative to be CMMI ML 3 compliant.
  • Value Streams (VSs) can be used to select subprocesses for statistical management.
  • Value Streams are representative of major lifecycle phases.
    • SEI is recommending for QPM that at least one subprocess be statistically managed within each major project phase and that at least one subprocess be included from each of the four CMMI Continuous Representation Categories (Process Management, Project Management, Engineering, and Support)
    • Statistically managed subprocesses should facilitate predicting process outcomes and tracking current project progress.
    • Peer Reviews could be one of these “control knobs”/subprocesses to manage statistically as it can appear in several Categories.
    • It may take two or more years to collect sufficient data to determine the critical subprocesses to optimize for ML 4.
value stream structure
Value Stream Structure
  • Overview of process
  • Identifies all associated sub processes
  • Provides for CMMI artifact collection
  • Includes other functionality (CM, ILS, etc.)

Installation Value Stream

CMMI ML 3 Process Areas

DAR

RSKM

REQM

CM

RD

TS

OT

IPM

PP

PMC

SAM

MA

PPQA

PI

VER

VAL

OPF

OPD

Pre-Install Phase

Install Phase

Closeout Phase

IDP

BESEP

Turnover

Site Survey

Install prep

Project initiation

Install Activities

Test & Checkout

Sub processes

qa cmmi structure
QA / CMMI Structure

Command Level Docs

RSKMP

CMP

SAM

PMP

SEP

QAP

M&A P

RMP

ILSP

COI/PM Level Docs

COI/Program Management Plan

Project Level Docs

Project /Assignments Plan

Value Streams (handbooks)

Project Plans tie

the COI to the VS

R & D VS

Acquisition VS

Integration VS

Installation VS

Life Cycle

ISEA VS

SSA VS

Repair VS

quality management system qms involving value streams1
Quality Management System (QMS) Involving Value Streams
  • The following Command processes complement and are embedded in the foregoing VSs:
    • Finance
    • Contracting
    • Purchasing
    • Business Processes
      • CMMI
      • QA
      • Etc.
  • Note: Logistics and Configuration Management may become VSs themselves if they are separate product/service deliverables to a customer in their own right.
lss focused efforts
LSS Focused Efforts
  • Black Belts will assist the Implementation of CMMI
    • Work with Divisions to determine VSs
    • Break VSs down into Process steps
  • Green Belts will conduct events to further define and improve VS Processes
  • Black Belts will support the EntPG Structure
  • Basic EntPG Communication Plan will provide visibility and coordination of these efforts
detailed communication plan
Detailed Communication Plan

EntPG

09K

Master BB

IPT

Chair

IPT

Chair

IPT

Chair

IPT

Chair

Dept

EPG

Dept BB

DIPT

Chair

DIPT

Chair

DIPT

Chair

DIPT

Chair

Div BB

Div

EPG

Div

EPG

Div

EPG

TWG

Chair

TWG

Chair

TWG

Chair

TWG

Chair

TWG

Chair

TWG

Chair

TWG

Chair

TWG

Chair

TWG

Chair

TWG

Chair

TWG

Chair

TWG

Chair

TWG

Chair

TWG

Chair

TWG

Chair

8 step process
8 Step Process

Identify &

Prioritize

Opportunities

Project

Definition

Document &

Measure

Current

Reality

Analyze

Waste &

Variation

  • The 8 Step Process is the improvement methodology based on tools and techniques of Lean & Six Sigma

1

2

4

3

Excellence

Implement

&

Validate

Improve

&

Innovate

Communicate &

Acknowledge

Success

Measure &

Sustain

8

6

5

7

purpose of measuring
Purpose of Measuring
  • Measurements should do any or all of the following:
    • Directly tie in to the project objectives
      • Assess current performance of your process against customer requirements
      • Show baseline (existing) capability
      • Validate project benefits and ensure visibility of improvements
    • Identify relative strengths and weaknesses in and between processes
    • Monitor and control long term performance
    • Be concise and readily understandable
      • Facilitate rapid understanding of what is happening in the process/project
establishing a measurement
Establishing a Measurement
  • Establishing a measurement follows a generic process
  • Five steps to establish an effective measurement:
    • Select the measurement
    • Define the measurement
    • Identify measurement/data source
    • Define a measurement collection/sampling plan
    • Maintain the measurement
select the measurement
Select the Measurement
  • The selection of effective measurements should consider data that is:
    • Relevant
      • Related to your purpose or goal and actually used
      • Is collected real time
    • Accurate
      • Measures what was intended to be measured
      • Obtained through careful reading and recording
    • Understandable
      • Clear and organized
      • Summarized in tables or graphically
    • Complete
      • Includes every necessary detail and event
      • Enables you to make decisions
    • Simple
      • Data is available without extraordinary effort
      • Data is not expensive to collect
measurement effectiveness
Measurement Effectiveness
  • Need to define measures to assess project complexity. Possible candidates areas:
    • Estimated engineering hours (not dollars which could change) Technology risks
    • Number of requirements and their volatility
  • Management has a role in driving down complexity in all phases of a project.
  • “More consideration must be paid to ways of reducing Project Challenge [Complexity]. Doing so is a major challenge prior to the establishment of the development project, beginning during the pre-acquisition period. Earlier application of Systems Engineering practices and principles may go a long way towards reducing that challenge.” Survey Report, p. 100
slide21
6s
  • In statistics, s represents standard deviation, a measure of variation for process performance
  • Sigma is generated by measuring processes
    • Process data can be collected and evaluated to determine its impact on productivity, performance, and customer satisfaction
    • The measurements provide the ability to “predict” process performance and provide a benchmark to determine if actions have produced results
operating at 6 capability implies
“Operating at 6 Capability” implies
  • Data driven decision making
  • Meeting customer’s requirements
  • Measurable processes
  • Processes Under Control
  • Variation has been reduced
  • Future performance can be predicted
  • Results of actions can be assessed
utilizing the data
Utilizing the Data
  • Process variation is large compared to specifications such that the process must remain centered to maintain capability
  • Any shifts in process mean, or variation, will abruptly reduce the capability of the process
    • Cp measures the ability of a distribution to fit within specs
      • Cp = (usl-lsl / 6s)
    • Cpk measures how well the process is centered
      • Cpk = min (usl-m / 3s, m-lsl / 3s)
utilizing the data1
Utilizing the Data
  • Cp and Cpk are used together so that they may indicate if the process can meet specs and is properly centered
  • Cp
  • Low variation
  • Centered Cp
  • Cpk High variation
  • Not Centered
  • Cpk
  • Cp
  • Low variation
  • Not Centered
  • Cpk

target

mean

USL

LSL

interpreting histograms
Process at Time Period A

Process at Time Period B

Detecting a process shift

Process Before Improvement

Process After Improvement

Interpreting Histograms
  • Histograms can judge current performance and future performance
slide26
Wrap
  • Six Sigma supports both individual process areas as well as aggregate process data
  • Six Sigma statistical processes should be applied to rolled up management level aggregate data as well as singular process data
  • Forecasting, modeling and prediction can be done utilizing statistically derived data
  • Six Sigma provides a tool set that can be used to collect and analyze data used in high maturity organizations
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