cmmi experiences

CMMI

Experiences.

Aug 27th, 2020

LyVo – QA Director

Who am I?

VO THI LY: Bachelor of Computer Science,

PSM1, CSQA, PMP, ISO 27001, GDPR, CMMI Dev

1.2, 1.3, 2.0 ML 5.

Leading in Optimizing process, policies to address the

business objectives.

My Quote: “Sharing is one of learning ways.”

Bachelor of Computer Science

Developers, Team Leader

Project Manager

QAM, QAD at NashTech

1997-2002

2002-2007

2007-2010

2010-Now

1. CMMI Introduction

2. Preparing for CMMI at each level

3. Optimizing – CMMI level 5

Outline

HERE WE GO !!

HERE WE GO !!

Resource Skills Examples

Understand the CMMI Real Improvement Planning/Do/Check/Act

History Dev 1.3 vs 2.0

1. CMMI Introduction

2. Preparing for CMMI at each level

3. Optimizing – Level 5

CMMI Introduction 1

1. CMMI Development History

2018 CMMI V2.0 Product Suite

2010 CMMI V1.3 (Be Stopped on Sep 30, 2020)

2006 CMMI V1.2 (Included CMMI-DEV)

2002 CMMI V1.1

2000 CMMI V1.02

1993 SW-CMM V1.1

1991 Software CMMI (SW-CMM) V1.0

1984 Carnegie Mellon University

Process unpredictable, poorly controlled and reactive

Process characterized for projects and is often reactive

Process characterized for the organization and is proactive

Process measuredand controlled

Focus on process improvement

4

1. CMMI Dev 1.3 vs 2.0

2.0 – Maturity Level1.3 – Maturity Level

1

2

3

4

5

Optimizing

QuantitativelyManaged

Performed

Managed

Defined

1. CMMI Dev 1.3 vs 2.0 (cont.)

1.3 – View 2.0 – View


Requirements Development and Management

(RDM)

Peer Review (PR)

Verification and Validation (VV)

Process Quality Assurance (PQA)

Technical solution (TS)

Product integration (PI)

Estimating (EST)

Planning (PLAN)

Monitor and Control (MC)

Risk and Opportunity Management

(ROM)Organizational Training (OT)

Decision Analysis and Resolution (DAR)

Configuration Management (CM)

Causal Analysis and Resolution (CAR)

Governance (GOV)

Implementation Infrastructure (II)

Managing Performance and

Measurement (MPM)

Process Asset Development (PAD)

Process Management (PM)

Imp

rovi

ng

Do

ing

Ma

nag

ing

Enab

ling

1.3 – Process Area Group 2.0 – Practice Area Group


1.3 – Process Area Component 1.3 – Practice Area Component


1.3 – Process Area 1.3 – Practice Area

CMMI Dev 2.0 – Appraisal Method

CMMI 1.3 – Appraisal Method

Randomly select projects belong to Appraisal Scope with fully checking all PA.

Subgroup Project

PI

Product

Integratio

n

TS

Technical

Solution

PQA

Process

Quality

Assuranc

e

PR

Peer

Reviews

RDM

Requirem

ents

Develop

ment and

Managem

ent

VV

Verificati

on and

Validatio

n

MPM

Managing

Performa

nce and

Measure

ment

PAD

Process

Asset

Develop

ment

PCM

Process

Managem

ent

RSK

Risk and

Opportun

ity

Managem

ent

OT

Organizat

ional

Training

EST

Estimatin

g

MC

Monitor

and

Control

PLAN

Planning

CAR

Causal

Analysis

and

Resolutio

n

CM

Configura

tion

Managem

ent

DAR

Decision

Analysis and

Resolution

HCM Project 1 RS RS SE SE SE SE SE SI SI SE SI SE SE SE SE SE SE

HCM Project 2 SE SE SE SE SE SE SE SI SI SE SI RS RS RS SE SE SE

HCM Project 3 SE SE SE SE SE SE SE SI SI SE SI SE SE SE SE SE SE

HN Project 4 SE SE RS RS RS RS SE SI SI SE SI SE SE SE RS RS RS

HN Project 5 SE SE SE SE SE SE SE SI SI RS SI SE SE SE SE SE SE

Senior Management &QA SI SI SE SI SI SI RS RS RS SI SI SI SI SI SI SI SI

Training SI SI SI SI SI SI SI SI SI SI RS SI SI SI SI SI SI

Sample Eligible (SE) Substituted From (SUB) Not Yet (NY) Added PA (ADD)

Sample Ineligible (SI) Substituted To (SUB) Randomly Sampled (RS)

PMW

Planning and Managing Work

SI

Supporting Implementation

EDP

Engineering and

Developing Products

ENQ

Ensuring Quality

IMP

Improving Performance

MBR

Managing

Business

Resilienc

e

MWF

Managing

the

Workforc

e


Preparing for CMMI at each level

2

Target CMMI

Why

How Who

What

2. Preparing for the CMMI at each level

Current Performance

Improvement, Optimizing

LEVEL 2,3Business Objectives

Lesson learnt

Best Practices

Data Trend

Actions for improvement LEVEL 4,5Using statistical and other quantitative

techniques to:

Determine the organization’s ability

Identify potential areas

Evaluate the effect of proposed

improvements on meeting BO & QPPO

Predict likelihood

2. Real Improvement?

2. Preparing for the CMMI at each level

2. Preparing for the CMMI 2,3

Create

Improvement PlanDeployment Pre-appraisal Appraisal

Purpose

Vision, Business Objective

Resource, Tool

Meeting, Report

Appraisal Scope

….

Gaps Analysis, Kickoff

Define Missing Practice Areas

Training to Project

Implement & Evaluation

Mapping with PA of CMMI (PIID)

for projects

Create Appraisal Plan with LA

Rehearsal with selected team

Prepare Performance

Traceability Report

Appraisal Performance Report

2. Key success factors

If management fails to enforce the “rules,” employees quickly recognize that the rules are unimportant

Staff

Expert/Process Owner

Expert/Process Owner

Senior Management

Executive Management Vision, Strategy

Business Objectives.

KPI

Process

Collect Data

Follow

Communicate

Communicate

Understand What, Why, How, When

Resource, Tools

Verify

Data Quality

Enforce, Training

Automated Self Other

Governance & Implementation Infrastructure

Persistence and Habitual

Optimizing – CMMI Level 5

3

3. Preparing for the CMMI level 4, 5

Current Performance

Improvement, Optimizing

LEVEL 2,3Business Objectives

Lesson learnt

Best Practices

Data Trend

Actions for improvement LEVEL 4,5Using statistical and other quantitative

techniques to:

Determine the organization’s ability

Identify potential areas

Evaluate the effect of proposed

improvements on meeting BO & QPPO

Predict likelihood

2. Preparing for the CMMI

Update PA at level 5

Defining/Updating Missing Process Areas:

Managing Performance & Measurement (MPM)

Causal Analysis & Resolution (CAR)

Governance

Plan

Process Management

Resources

Measurement Systems

Statistic Analysis Tool: Minitab, Crystal Ball, Excel, etc

PM & Senior Management: Understand Statistic analysis basic and advance.

Study prediction model: such as increasing Productivity

Performance Analysis

Baseline Current Performance

Set Target for BO

Make Improvement

Tracking, Tracingperformance

3. Optimizing – Level 5 Preparation

1. Problem Statement : To consider and propose the common framework and library to create the project

skeleton and overcome the MSA/Cloud native related challenges better to Propose the innovation for

organization in 2020 as one of actions after evaluating Business Objectives 2019.

0.320.300.280.260.240.220.200.18

5.0

4.9

4.8

4.7

4.6

S 0.0455903

R-Sq 89.1%R-Sq(adj) 86.9%

Overall Productivity

CSS

The relationship between CSS and Overall Productivity 2019CSS = 4.094 + 2.868 Overall Productivity

0.320.300.280.260.240.220.200.18

0.38

0.36

0.34

0.32

0.30

S 0.0103445

R-Sq 85.6%R-Sq(adj) 82.7%

Overall Productivity

GP

The relationship between Overall Productivity and GP 2019GP = 0.2029 + 0.5561 Overall Productivity

3.Optimizing –An Example of Measurement Performance

2. Problem Analysis: With collecting data of project MSA cloud native from Jan 2019 to Mar 2020 as

below info:

Descriptive Statistics: Overall Productivity-MSA

Statistics

Variable N N* Mean SE Mean StDev Minimum Q1 Median Q3

Overall Productivity-MSA 14 0 0.2115 0.0163 0.0609 0.1325 0.1773 0.1938 0.2468

Variable Maximum

Overall Productivity-MSA 0.3408

The median of overall productivity is about

0.1938, it means there are about 50% projects

less than the company target 0.21 (USP/Pd).

If using this baseline to apply in the model to

predict how much percentage of certainty to

achieve target 0.21 USP/person day overall

productivity 2019 as following

3.Optimizing- An Example of Measurement Performance (cont.)

2. Problem Analysis: With collecting data of project MSA cloud native from Jan 2019 to Mar 2020 as

below info:

The regression equation is Overall Productivity = - 0.04228 + 0.5757 Coding Productivity

0.600.550.500.450.400.350.30

0.35

0.30

0.25

0.20

0.15

0.10

S 0.0309588

R-Sq 76.1%

R-Sq(adj) 74.1%

Coding Productivity

Overa

ll P

rod

ucti

vit

y

Fitted Line PlotOverall Productivity = - 0.04228 + 0.5757 Coding Productivity

Current - Median Expectation Increasing

Overall Productivity 0.194 0.21 8.25%

Coding Productivity 0.433 0.582632794 34.56%

With this analysis base on the data from Jan 2020

Mar 2020 of baseline MSA project using cloud

native, to increasing median of overall productivity

from 0.19 to 0.21, the coding productivity should

increase 34.56%.


# Activities Planned

Date

Actual

Date Responsibility Participants Remarks

1 Initial Data Analysis Jan 20 Mar 20 QA DM, TD, QA

2 Process Analysis Jan 20 Mar 20 DM, SWAT, QA DM, TD, QA

3 Root Cause Analysis Jan 20 Mar 20 DM, SWAT, QA DM, SWAT, QA

4 Solution selection

and Action Planning

Feb 20 Apr 20 DM, SWAT, QA PM+QA

5 Project Piloting May 20 Aug 20 DM, SWAT, QA PM+QA

6 Pilot Evaluation Aug 20 Sep 20 PM+QA PM+ QA

7

Deployment project selection & action

suggestion

Sep 20 Dec 20 DM, SWAT, QA QA, DM Will plan af ter pilot

evaluation

8 Deployment

Evaluation

Dec 20 Dec 20 PM + QA QA

3. Action Plan 4. Data Collection Plan

What to Measure? How to Measure? Who will

Measure?

Operational

Def inition

Measureme

nt Method

Data collection

Method and Location

Data collection

Frequency

Persons

Assigned

Effort of coding

and product

integration/ Size

USP/

person day

Size (completed

USP) / Coding

actual Effort

At end of

every

sprint

PM + QA

# USP of the

sprint

USP Size (completed

USP)

At end of

every

sprint

PM

(Revenue –

Cost of goods

sold) *100/

Revenue

% Finance team

(since this is

sensitive data)

Monthly QA


5. Root causes:

The coding effort distribution from the MSA projects has lower productivity than target as following:

This If Develop the common framework to cover common structures of those projects, i can saving efforts as following

Total Coding Effort (Hour) 8096 Saving effort to see how much coding productivity increasing

Common Structures (login modules, Logging and Tracking, Caching, User Management) 1943.0 24% 84.00% 20%

Rework 1619.2 20% 12% 8%

Training MSA Cloud Native (10days per person) 809.6 10% 70% 7%

Others 3724.2 46%

Grand Total 100% Total Saving 35.16% Coding productivity increasing expectation 34.56% 0.60%


Summary

CMMI 1.3 & 2.0 2010 CMMI V1.3 – Be Stopped on Sep 30, 2020

2018 CMMI V 2.0 – Practice Areas, Change Appraisal Method

Preparing for the CMMI at each level Executive Management, Senior Management to define vision, strategy, Business

Objectives

Training, Communicate with staff about Intent, value of Practice Area

Optimizing Process at level 5 Resources: Understand Statistic Technique, statistic analysis, Prediction Model

Preparing: Performance Improvement to meet Business Objectives

Further info: https://cmmiinstitute.com/

https://cmmiinstitute.com/

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