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Lean Six Sigma Master Black Belt Online Certification & Training

Lean Six Sigma Master Black Belt (Online)

April

48 Hours E-Learning +
56 Hours Project Mentoring


April 07 - May 26
E-Learning at your comfort
19:00 - 22:00 IST
Project Mentoring
(Sunday Only)


Project Mentoring Dates
Apr
Sun
07
 
Sun
14
 
Sun
21
 
Sun
28
May
Sun
05
 
Sun
12
 
Sun
19
 
Sun
26
E-Learning

₹30,800

E-Learning + Project Mentoring

₹38,800

E-Learning + Project Mentoring + Live Project

₹48,800

April

48 Hours E-Learning +
56 Hours Project Mentoring


April 21 - June 09
E-Learning at your comfort
19:00 - 22:00 IST
Project Mentoring
(Sunday Only)


Project Mentoring Dates
Apr
Sun
21
 
Sun
28
May
Sun
05
 
Sun
12
 
Sun
19
 
Sun
26
Jun
Sun
02
 
Sun
09
E-Learning

₹30,800

E-Learning + Project Mentoring

₹38,800

E-Learning + Project Mentoring + Live Project

₹48,800

6 Reasons to choose Lean6SigmaPro

World's 1st Live Project Based Experential Learning
Curriculum with maximum hours of training & Minitab practice in the industry
Get trained by high paid Lean Six Sigma Consultants
Unlimited post-certification support
Courses aligned to Exemplar Global, TÜV & SÜD, ASQ, IASSC, KPMG & ISO
100% Certification guaranteed + Project certificate


Lean Six Sigma Master Black Belt

A Certified Master Black Belt is a highly qualified professional with the most advanced knowledge and certification in Lean Six Sigma methodology. They are responsible for leading the Lean Six Sigma journey within an organization and ensuring that the methodology is utilized effectively throughout all processes. The role of a Lean Six Sigma Master Black Belt is crucial to the success of the organization's Lean Six Sigma initiatives.


This role involves leading the Six Sigma program, mentoring other Six Sigma practitioners, and designing and implementing continuous improvement projects throughout the organization. It is a position of leadership.


The course includes,

  • 80+ hours of High-Quality E-learning
  • 120+ hours of project Mentoring (6 projects)
  • 100+ Business scenarios


80+ hours of high-quality E-learning help you master the concepts of Lean Six Sigma coupled with sound knowledge of statistics. You can also use your E-learning as a refresher as necessary for one year.


To become a Lean Six Sigma architect in an organization, one must have mastery in executing Lean Six Sigma projects. Apart from possessing good DMAIC knowledge, a Master Black Belt should also have efficient business acumen and leadership skills to lead the Lean Six Sigma journey in the organization. Project mentoring sessions are intended to assist professionals in gaining essential experience and knowledge for driving Lean Six Sigma initiatives in their workplace.


As a Lean Six Sigma Master Black Belt, one of your main responsibilities is to provide guidance and support to Green Belts and Black Belts. To do this effectively, you must have a keen understanding of business scenarios and the ability to apply Lean Six Sigma methodologies. By familiarizing yourself with over 100 business scenarios, you will be well-prepared to mentor your GBs and BBs.

Duration
200 Hours: 80 of E-Learning + 120 Hours of Project Mentoring
Certification
We help you with internationally recognized certification.
Objective
Our objective is to prepare architects of Lean Six Sigma who can drive Lean Six Sigma initiatives in their organizations.
Who Should Attend?
  • Certified Black Belts with a minimum of five project experience
  • Any professional seeking to accelerate their corporate career
  • Anyone who wants to consider Lean Six Sigma as a career option
  • Certified Master Black Belts would like to transform themselves as Architects of Lean Six Sigma.
Project Assistance
We provide mentorship for you to drive Lean Six Sigma projects.
Essentials
Certified Green Belts with a minimum of 1 year as Green Belt, or professionals with over four years of industry experience.
Trainers Profile

    Srinivas TV - Click to view full profile

  • Certified Master Black Belt & a passionate trainer
  • Over 20 years in the field of Lean Six Sigma
  • Executed/Mentored over 300 Lean Six Sigma projects with $30+ Saving.
  • Trained over 5000 professionals across industries.
  • Corporate Lean Six Sigma trainer for fortune 50 Companies
Course Fee Includes
  • 80+ hours of High-Quality E-learning
  • 120+ hours of project Mentoring (6 projects)
  • 100+ Business scenarios
  • One year access to E-Learning portal
  • Sample question papers with solutions
  • Examination & Certification cost
  • Unlimited post certification support
  • Exclusive invite to attend Six Sigma project presentations.
  • Mentorship & assistance to accelerate your corporate career.
  • 100% Placement assistance
Course Program
  • 1.0 Introduction to Lean
  • 2.0 What is Lean & Application of Lean
  • 3.0 6S Before Lean(Simulation to Understand)
  • 4.0 Types of Waste – (Videos &Simulation to Understand)
  •    4.1 Different Types of Wastes
  •    4.2 Causes of Waste
  •    4.3 Remedies of Waste
  • 5.0 Lean Principles Introduction
  •    5.1 Identify Customers & Specify Value
  •    5.2 Value Stream Mapping
  •    5.3 Create Flow
  •    5.4 Respond to Pull
  •    5.5 Pursuit Perfection
  • 6.0 Identify Customers & Specify Value
  •    6.1 Customer – Internal & External
  •    6.2 Value Added & Non-Value Added (Simulation to Understand)
  • 7.0 Create Value Stream Mapping (VSM) (Simulation to Understand)
  •    7.1 Terminologies (CT, FTY, RTY, CO, TPT, WIP, WIQ)
  •    7.2 Process Efficiency
  •    7.3 Customer Takt time
  •    7.4 Create VSM(Simulation to Understand)
  •    7.5 Process Efficiency
  • 8.0 Create Value Stream Design (VSD) (Simulation to Understand)
  • 9.0 Create Flow & Respond to Pull (Simulation to Understand)
  •    9.1 Single Piece Flow (Simulation to Understand)
  •    9.2 Single Minute of Exchange of Dies(Simulation to Understand)
  •    9.3 Line Balancing (Simulation to Understand)
  •    9.4 Kanban (Pull Production) (Simulation to Understand)
  •    9.5 Heijunka (Production Levelling)(Simulation to Understand)
  •    9.6 Just In Time(Simulation to Understand)
  • 10.0 Additional Lean Tools
  •    10.1 Spaghetti Diagram
  •    10.2 Circle Diagram
  •    10.3 Total Productive Maintenance
  •    10.4 Andon & Visual Management
  •    10.5 Visual Factory
  •    10.6 Gemba
  •    10.7 Hoshin Kanri (Policy Deployment)
  •    10.8 PDCA (Plan Do Check Act)
  •    10.9 Poka-Yoke (Mistake Proofing) (Simulation to Understand)
  •    10.10 Root Cause Analysis
  •    10.11 Standardized Work (Simulation to Understand)
  •    10.12 Theory of Constraints (Introduction)
  • 1.0 Introduction to Quality
  • 2.0 Quality Leaders (Juran, Deming, Shewhart, Ishikawa) (Videos to Understand)
  • 3.0 Cost of Quality (COQ)
  • 4.0 Cost of Poor Quality (COPQ) (Videos to Understand)
  • 5.0 Optimum Quality Levels
  • 6.0 Failure Mode & Effect Analysis (FMEA)
  •    6.1 Create Process FMEA (Simulation to Understand)
  •    6.2 Create Design FMEA
  • 7.0 Key Performance Measures
  •    7.1 Key Performance Indictors
  •    7.2 Customer Satisfaction
  •    7.3 Product Differentiation
  •    7.4 Customer Loyalty Metrics
  •    7.5 Leading & Lagging Indicators
  •    7.6 Create Line of Sight
  • 8.0 Key Business Drivers & their Impact
  •    8.1 Profit/Margin (Practice to Understand)
  •    8.2 Market Share
  •    8.3 Net Present Value (NPV)
  •    8.4 Cost Benefit Analysis (CBA)
  •    8.5 Hard & Soft Benefits (Practice to Understand)
  •    8.6 Cost avoidance & Cost reduction (Practice to Understand)
  • 9.0 Organisation Goals & Six Sigma
  • 10.0 Balanced Score Card& Six Sigma
  • 11.0 History & Evolution of Six Sigma
  • 12.0 Continuous Improvement
  • 13.0 Basics of Six Sigma (Simulation to Understand)
  • 14.0 Six SigmaApplications
  • 15.0 Types of Six Sigma Projects
  •    15.1 DMAIC
  •    15.2 DFSS (DMADV/IDOV)
  • 16.0 Organization Road Blocks
  •    16.1 Organisation Structure & Culture
  •    16.2 Common Causes of Six Sigma Failures
  •    16.3 Stakeholder Analysis (Six Sigma Impact)
  • 17.0 Change Management (Simulation & Videos to Understand)
  •    17.1 Basics of Change Management
  •    17.2 Readiness Assessment
  •    17.3 Communication Plans to Overcome Barriers
  • 18.0 Strategic Planning & Deployment
  •    18.1 Importance of Lean Six Sigma
  •    18.2 Hoshin Kanri (Policy Deployment) (Practice to Understand)
  •    18.3 SWOT Analysis (Practice to Understand)
  •    18.4 PEST
  •    18.5 Business Contingency Planning
  • 19.0 Team Management (Simulation & Videos to Understand)
  •    19.1 Team Types & Constraints
  •    19.2 Team Roles &Responsibilities
  •    19.3 Team Member Selection Criteria
  •    19.4 Team Success Factors
  • 20.0 ProjectTeam Dynamics (Simulation to Understand)
  •    20.1 Forming
  •    20.2 Storming
  •    20.3 Norming
  •    20.4 Performing
  •    20.5 Team Communication
  • 21.0 Team Facilitation
  •    21 Motivational Technique
  •    22 Team Stages & Development
  •    23 Team Communication
  •    24 Team Leadership & Models
  • 22.0 Team Dynamics (Simulation & Videos to Understand)
  •    22.1 Group Behaviour
  •    22.2 Meeting Management
  •    22.3 Team Decision Making Methods
  • 23.0 Team Training (Simulation to Understand)
  •    23.1 Need Assessment
  •    23.2 Delivery
  •    23.3 Evaluation
  • 1.0 Voice of Customer & Business(Simulation to Understand)
  •    1.1 Collect Customer & Business Voices
  •    1.2 Eliminate Vagueness & Ambiguity
  •    1.3 VOC Clarity Table
  • 2.0 Kano Model (Practice to Understand)
  • 3.0 Benchmarking
  •    3.1 Competitive
  •    3.2 Collaborative
  •    3.3 Best Practices
  • 4.0 Customer Requirements to Process Requirements
  •    4.1 Critical to X (X-Quality, Cost, Safety or any other )
  •    4.2 CTQ Drill Down
  •    4.3 Quality Function Deployment (Practice to Understand)
  • 5.0 Project Section & Prioritisation (Practice to Understand)
  • 6.0 Process Owners & Stakeholder Analysis
  • 7.0 Project Charter (Practice to Understand)
  •    7.1 Business Case
  •    7.2 Problem Statement
  •    7.3 Project Goal Statement
  •    7.4 Project Team
  •    7.5 Project Timeline
  •    7.6 Project Scope
  •    7.7 Expected Benefits
  • 8.0 Financial Evaluation & Business Case
  • 9.0 Develop Project Metrics
  • 10.0 Project Short &Long Terms Gain (Practice to Understand)
  • 11.0 Project Risk Analysis
  • 12.0 Six Sigma Project Types
  • 13.0 ProjectRoles & Responsibilities
  •    13.1 Roles of Executive Leadership
  •    13.2 Roles of Champion
  •    13.3 Roles of Sponsor
  •    13.4 Roles of Master Black Belt
  •    13.5 Roles of Black Belt
  •    13.6 Roles of Green Belt & Team
  • 14.0 Project Managements & Analytical tools
  •    14.1 Gantt charts
  •    14.2 Work Breakdown Structure
  •    14.3 Critical Path Method (CPM) (Simulation to Understand)
  •    14.4 Project Evaluation & Review Technique
  •    14.5 RACI model
  •    14.6 Activity Network Diagram
  •    14.7 Tree Diagram
  •    14.8 Matrix Diagram
  • 15.0 Project Scope
  • 16.0 SIPOC & Process Mapping (Simulation to Understand)
  • 17.0 Project Performance Measurement
  •    17.1 Define Performance Measurement
  •    17.2 Process Critical Elements
  •    17.3 Key Outputs
  • 18.0 Project Tool Gate Review
  • 1.0 Process Analysis & Documentation
  •    1.1 Process Flow Charts
  •    1.2 Work Instructions &Gap Analysis
  • 2.0 Types of Data & Measurement Scale (Practice to Understand)
  •    2.1 Continuous (Variable) Data
  •    2.2 Discrete (Attribute) Data
  •    2.3 Nominal Data
  •    2.4 Ordinal Data
  •    2.5 Interval Measurement
  •    2.6 Ratio Measurement
  • 3.0 Population & Sampling
  •    3.1 Basics of Sampling
  •    3.2 Calculate Sample size(Practice to Understand)
  • 4.0 Type of Samples(Simulation to Understand)
  •    4.1 Random Sample
  •    4.2 Systematic Sample
  •    4.3 Stratified Sample
  • 5.0 Basics of Statistics (Simulation to Understand)
  •    5.1 Central Tendency
  •    5.2 Dispersion
  •    5.3 Proportion
  • 6.0 Introduction to Statistical Software (Minitab)
  •    6.1 Minitab Practice
  •    6.2 Descriptive Statistics
  •    6.3 Inferential Statistics
  • 7.0 Probability
  •    7.1 Basic Concepts
  •    7.2 Independence Events
  •    7.3 Mutually Exclusive Events
  •    7.4 Addition & Multiplication Rules
  •    7.5 Complimentary Probability
  •    7.6 Occurrence of events
  • 8.0 Statistical Distributions (Practice to Understand)
  •    8.1 Normal
  •    8.2 Binominal
  •    8.3 Poisson
  •    8.4 Chi-Square
  •    8.5 Student’s T
  •    8.6 F distribution
  •    8.7 Hypergeometric
  •    8.8 Bivariate
  •    8.9 Exponential
  •    8.10 Lognormal
  •    8.11 Weibull
  • 9.0 Probability of Distributions (Practice to Understand)
  •    9.1 Frequency Distribution
  •    9.2 Cumulative Frequency Distribution
  •    9.3 Inverse Cumulative Frequency Distribution
  • 10.0 Central Limit Theorem (Simulation to Understand)
  • 11.0 Measurement & Data Collection
  •    11.1 What is Measurement
  •    11.2 Operation Definition
  • 12.0 Data Collection Plan (Simulation to Understand)
  •    12.1 Check Sheets
  •    12.2 Data Coding
  •    12.3 Data Cleaning
  •    12.4 Data Collection Pitfalls
  •    12.5 Avoid Data Collection Pitfalls
  •    12.6 Seasonality Effect on Data
  •    12.7 Data Collectors Training
  • 13.0 Data Mining
  • 14.0 Data Preparation
  • 15.0 Graphical Analysis (Practice to Understand)
  •    15.1 Pareto
  •    15.2 Scatter Plot
  •    15.3 Box Plot
  •    15.4 Histogram
  •    15.5 Stem &Leaf Plots
  •    15.6 Time Series Plot
  •    15.7 Run Chart
  •    15.8 Normality (using Minitab)
  •    15.9 Graphical Summary
  • 16.0 Metrology
  •    16.1 Elements of Metrology
  •    16.2 Calibration System
  •    16.3 Traceability &Reference Standards
  •    16.4 Control & Integrity of Standards
  • 17.0 Variations& Measurement System Analysis
  •    17.1 Understanding Variations (Simulation to Understand)
  •    17.2 Measurement System Analysis (MSA)
  •       17.2.1 Discrimination
  •       17.2.2 Accuracy
  •       17.2.3 Precision
  •       17.2.4 Stability
  •    17.3 GRR for Continuous data (Simulation to Understand)
  •    17.4 GRR for Discrete Data (Simulation to Understand)
  •    17.5 Destructive Measurement System
  •    17.6 Control Charts & Stability (Simulation to Understand)
  •       17.6.1 I-Chart
  •       17.6.1 I-MR Chart
  •       17.6.1 X-Bar R Chart
  •       17.6.1 X-Bar S Chart
  •       17.6.1 C Chart
  •       17.6.1 U Chart
  •       17.6.1 NP Chart
  •       17.6.1 P Chart
  • 18.0 Sporadic problems
  • 19.0 Measurement Systems to
  •    19.1 Sales & Marketing
  •    19.2 Engineering
  •    19.3 Supply chain & Management
  •    19.4 Research & Development
  •    19.5 Customer Satisfaction
  • 20.0 Baseline Process Performance (Practice to Understand)
  •    20.1 Baseline Discrete Data (DPU, DPO,DPMO)
  •    20.2 Baseline Continuous Data (Cp, Cpk, Pp, Ppk, Cpm)
  •    20.3 Sigma Value (Short term & Long term)
  •    20.4 Sigma Shift (Short term Vs Long term)
  • 21.0 Process Capability in Detail (Practice to Understand)
  •    21.1 Natural Process Limits & Specification Limits
  •    21.2 Design & Conducting Process Capability Studies
  •    21.3 Specifications, Sampling Plan, Stability & Normality
  •    21.4 Capability for Normal & Non-Normal Data
  •    21.5 Process Performance (PPM, DPU, DPMO)
  •    21.6 Transformations (Box-Cox & Johnson transformation)
  •    21.7 Capability for Discreet Data
  • 1.0 Identify Potential Causes (Practice to Understand)
  •    1.1 Brain Storming
  •    1.2 Affinity Diagram
  •    1.3 Cause & Effect Diagram
  •    1.4 Five Whys?
  •    1.5 Fault tree analysis
  • 2.0 Tabular Analysis
  • 3.0 Process Analysis
  •    3.1 Value Stream Mapping (Recap from Lean)
  • 4.0 Data Analysis
  • 5.0 NormalCurve & Normality Test(Practice to Understand)
  • 6.0 Outlier Analysis
  • 7.0 Data Normalisation
  • 8.0 Confidence Interval, Risk & P value
  • 9.0 Hypothesis Testing -Null & Alternate
  •    9.1 Significance of Confidence Level
  •    9.2 Significance of Power
  •    9.3 Statistical &Practical Significance
  •    9.4 Sample Size for Hypothesis Tests
  •    9.5 Point & Interval Estimates
  •    9.6 Contingency Tables
  • 10.0 Alpha & Beta Risks (Practice to Understand)
  • 11.0 Hypothesis with Normal Data(Practice to Understand)
  •       11.1 One Sample T Test
  •       11.2 Two Sample T Test
  •       11.3 Paired T Test
  •       11.4 One-Way Anova
  •       11.5 Test of Variance
  •          11.5.1 One Variance Test
  •          11.5.2 Two Variance Test
  • 12.0 Hypothesis with Non- Normal Data(Practice to Understand)
  •       12.1 1 Sample Sign
  •       12.2 1 Sample Wilcoxon
  •       12.3 Mann – Whitney
  •       12.4 Kruskal- Wallis
  •       12.5 Mood’s Median
  • 13.0 Hypothesis with Discrete Data (Practice to Understand)
  •    13.1 1 Proportion
  •    13.2 2 Proportions
  •    13.3 Chi-Square
  • 14.0 Multi Vari Chart (Practice to Understand)
  • 15.0 Correlation & its Terminologies (Practice to Understand)
  • 16.0 Correlation &Causation (Practice to Understand)
  • 17.0 Regression Analysis (Practice to Understand)
  • 18.0 Linear & Non-Linear Regression (Practice to Understand)
  • 19.0 Simple & Multi-Linear Regression (Practice to Understand)
  • 20.0 Residual Analysis (Practice to Understand)
  • 21.0 Predicting Modelling using Classification and Regression Tree
  • 22.0 Logistic Regression Analysis
  • 23.0 Anova
  •    23.1 One Way Anova
  •    23.1 Two Way Anova
  •    23.1 General Linear Model
  • 24.0 Chi-Square Test (Practice to Understand)
  • 25.0 Multivariate Tools (Practice to Understand)
  •    25.1 Factor Analysis
  •    25.2 Item Analysis
  •    25.3 Discriminant Analysis
  •    25.4 Simple & Multiple Correspondence Analysis
  • 26.0 Exploratory Data Analysis
  • 27.0 Queuing theory
  • 28.0 Reliability Theory
  • 29.0 Qualitative analysis
  • 30.0 Design of Experiments (Practice to Understand)
  •    30.1 Need for DOE
  • 31.0 Terminologies
  •    31.1 Factors, Levels, Response, Treatment
  •    31.2 Blocks, Randomisation, Effects & Replication
  •    31.3 DOE Plots: Main Effect & Interaction Plots
  •    31.4 Confounding
  • 32.0 DOE Designs
  •    32.1 Full Factorial Experiments (Practice to Understand)
  • 33.0 Fractional Factorial (Practice to Understand)
  • 34.0 Latin Square Designs
  • 35.0 Balanced & Orthogonal Arrays
  • 36.0 Taguchi’s Design
  • 37.0 Confounding
  • 1.0 Generate & Evaluate Ideas (Simulations to Understand)
  •    1.1 Brain Storming
  •    1.2 SCAMPER
  •    1.3 Six Thinking Hats
  •    1.4 Benchmarking
  •    1.5 doHow
  •    1.6 Lean Solutions
  •    1.7 TRIZ (Practice to Understand)
  • 2.0 Selecting Best Solution(Practice to Understand)
  •    2.1 Multi-Voting
  •    2.2 Pay-off Matrix
  •    2.3 Criteria Matrix
  • 3.0 Pugh Matrix
  • 4.0 Force Field Analysis
  • 5.0 Solution Prioritization matrix
  • 6.0 Error Proofing
  •    6.1 Prevention & Detection
  •    6.2 Mistake Proofing &Examples
  • 7.0 Assess Risk FMEA (Recap)
  • 8.0 Piloting & Implementation
  •    8.1 Pilot Solutions
  •    8.2 Pilot Location
  •    8.3 Pilot Success Criteria
  • 9.0 Implementation
  •    9.1 Plan for implementation
  •    9.2 Stakeholder Analysis
  •    9.3 Communication Plan
  •    9.4 Implementation
  • 10.0 Change Management
  •    10.1 Techniques to gain commitment
  •    10.2 Techniques to overcome organizational barriers
  •    10.3 Necessary organizational structure for deployment
  •    10.4 Communications with management
  • 11.0 Organizational culture
  • 1.0 What is Control or Sustain?
  • 2.0 Types of Control
  •    2.1 Process Control
  •    2.1 Visual Controls
  • 3.0 Different Types of Process controls
  • 4.0 Response Plan & Reaction Plan
  • 5.0 Automated Process Control
  • 6.0 Statistical Process Control (Practice to Understand)
  •    6.1 Monitoring, Controlling of Process Performance
  •    6.2 Identify & Select Critical Process Parameters
  •    6.3 Subgrouping & Rational Subgrouping
  •    6.4 SPC- Continuous Data (I-MR, Xbar R, X bar S)
  •    6.5 SPC – Discrete Data (C,U,P,NP charts)
  • 7.0 Monitoring, Controlling of Process Performance
  • 8.0 Identify & Select Critical Process Parameters
  • 9.0 Subgrouping & Rational Subgrouping
  • 10.0 SPC- Continuous Data (I-MR, Xbar R, X bar S)
  • 11.0 SPC – Discrete Data (C, U, P, NP charts)
  • 12.0 Uniformly Moving Average Chart
  • 13.0 Exponentially Weighted Moving Average
  • 14.0 CUSUM chart
  • 15.0 Analyse Control Charts
  • 16.0 Control Plan
  • 17.0 Visual Control
  • 18.0 Sustain Improvements
  •    18.1 Lesson Learnt
  •    18.2 Documentation
  •    18.3 Trainings
  •    18.4 Ongoing Evaluation
  • 19.0 Benefit Computation
  • 20.0 Project Closure
  •    20.1 Lesson Learnt
  •    20.2 Documentation
  •    20.3 Trainings
  •    20.4 Ongoing Evaluation
  • 21.0 Celebration
  • 1.0 Common DFSS/ DMADV Methodologies
  •    1.1 Define
  •    1.2 Measure
  •    1.3 Analyze
  •    1.4 Design
  •    1.5 Validate
  • 2.0 Design for X (DFX)
  •    2.1 Design Constraints
  •    2.2 Design Cost
  •    2.3 Design for Manufacturability
  •    2.4 Design for Test
  •    2.5 Design for Maintainability
  • 3.0 Robust Design
  •    3.1 Robust Product Design
  •    3.2 Tolerance for Design
  •    3.3 Statistical Tolerancing
  •    3.4 Robust Process Design
  • 1.0 Strategies for Implementing Lean Six Sigma
  • 2.0 Balance Score Card (Practice to understand)
  • 3.0 Pipeline creation of new projects
  • 4.0 Develop governance documents, tracking tools,
  • 5.0 Project Alignment with a strategic plan
  • 6.0. Project alignment with business objectives
  • 7.0 Resource planning
  • 8.0 Resource development (Train & Mentor)
  • 9.0 Belt coaching and mentoring
  • 10.0 Project reviews
  • 11.0 Team facilitation and meeting management
  • 12.0 non-belt coaching and mentoring
  • 13.0 Execution
  • 14.0 Systems thinking
  • 15.0 Organizational culture
  • 16.0 Development of Maturity Models
  • 17.0 Organizational dynamics
  • 18.0 Intervention styles
  • 19.0 Interdepartmental conflicts
  • 20.0. Leadership and communication
  • 21.0 Business Transformation
  • 22.0 Business Process Management
  • 23.0 RPA Implementation

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