159 Courses in London

This one day masterclass is designed to provide a practical application of the content that is covered within The DEI Playbook and is aimed at anyone tasked with launching and implementing diversity and inclusion within their organisation.

APM Project Management Qualification (PMQ) The APM Project Management Qualification (PMQ) (IPMA Level D) is a knowledge-based qualification that allows candidates to demonstrate knowledge of all elements of project management. Candidates will be able to demonstrate an understanding of how these elements interact and how their project fits into their strategic and commercial environment. The course will cover the 67 assessment criteria defined by APM and prepare you to sit the examination on the fifth and final day. In addition to the instructor-led sessions, you should also expect to complete some self-directed study in the evenings. The APM Project Management Qualification (PMQ) examination is a three-hour paper where candidates must answer 10 out of 16 questions that can cover all 67 assessment criteria topics. What you will Learn You'll learn how to: Provide organizations with a proven project management methodology that will allow individuals to plan, organize, and control the successful implementation of projects Achieve the APM Project Management Qualification (PMQ), the UK's leading project management qualification Provide practical skills and techniques to help further your career in project management Getting Started Introductions Course structure Course goals and objectives Overview of the APM Project Management Qualification (PMQ) examination Structure of Organizations and Projects Organization structures Project sponsorship Organization roles Project Office Governance Legislation Project Lifecycle Project Lifecycles Handover and closure Project reviews Situational Context of Projects Project Management Programme Management Portfolio Management The Project Environment Communication Communication Conflict Management Negotiation Leadership and Teamwork Leadership Teamwork Planning for Success Business Case Investment Appraisal Success and Benefits Management Information Management and Reporting Project Management Plan Estimating Earned Value Management Stakeholder Management Scope Management Scope Management Requirements Management Change Control Configuration Management Schedule and Resource Management Schedule Management Resource Management Budgeting and Cost Management Procurement Procurement Contracts Provider Selection and Management Risk Management and Issue Management Risk Management Issue Management Quality Management and Examination Preparation Quality Management Preparation and Examination Preparation and examination briefing APM Project Management Qualification (PMQ) examination

APM Project Management Qualification (PMQ): In-House Training The APM Project Management Qualification (PMQ) (IPMA Level D) is a knowledge-based qualification that allows candidates to demonstrate knowledge of all elements of project management. Candidates will be able to demonstrate an understanding of how these elements interact and how their project fits into their strategic and commercial environment. The course will cover the 67 assessment criteria defined by APM and prepare you to sit the examination on the fifth and final day. In addition to the instructor-led sessions, you should also expect to complete some self-directed study in the evenings. The APM Project Management Qualification (PMQ) examination is a three-hour paper where candidates must answer 10 out of 16 questions that can cover all 67 assessment criteria topics. What you will Learn You'll learn how to: Provide organizations with a proven project management methodology that will allow individuals to plan, organize, and control the successful implementation of projects Achieve the APM Project Management Qualification (PMQ), the UK's leading project management qualification Provide practical skills and techniques to help further your career in project management Getting Started Introductions Course structure Course goals and objectives Overview of the APM Project Management Qualification (PMQ) examination Structure of Organizations and Projects Organization structures Project sponsorship Organization roles Project Office Governance Legislation Project Lifecycle Project Lifecycles Handover and closure Project reviews Situational Context of Projects Project Management Programme Management Portfolio Management The Project Environment Communication Communication Conflict Management Negotiation Leadership and Teamwork Leadership Teamwork Planning for Success Business Case Investment Appraisal Success and Benefits Management Information Management and Reporting Project Management Plan Estimating Earned Value Management Stakeholder Management Scope Management Scope Management Requirements Management Change Control Configuration Management Schedule and Resource Management Schedule Management Resource Management Budgeting and Cost Management Procurement Procurement Contracts Provider Selection and Management Risk Management and Issue Management Risk Management Issue Management Quality Management and Examination Preparation Quality Management Preparation and Examination Preparation and examination briefing APM Project Management Qualification (PMQ) examination

Overview This project is intended for managers to know a way to prepare and arrange comes, and meet the deadlines the side of dominant their budget. it'll facilitate in saving time and cash for the delegates through increased schedules, improved plans and communications. This project is intended for managers to know a way to prepare and arrange comes, and meet the deadlines the side of dominant their budget. it'll facilitate saving time and cash for the delegates through increased schedules, improved plans and communications. This course may be quick paced comes that's designed to fulfil the fast wants of the managers. It includes the fundamental principles and terms of Project Management with a straightforward set of tools and self-check tools. These tools facilitate managers to arrange their projects exactly.

Overview To understand the course thoroughly, you need to understand the practical application of the theory along with case studies as well as relevant examples. IT Project Management course will include those areas in managing the processes and activities related to guaranteeing the success of IT projects.

About this Virtual Instructor Led Training (VILT)  Conducted in an interactive manner, Exploration Project Management will include presentations by the course leader, syndicate and plenary exercises, and (optional) assessment of selected participants' projects. Industry case studies will be integrated into all the presentations. The course material will include a course manual (handout) and a course workbook (for exercises). Participants are requested to bring a mini-poster (two PowerPoint slides) as background material for discussion during the course. Training Objectives By the end of this Virtual Instructor Led Training (VILT), participants will be able to: Improve the evaluation, execution and delivery of exploration projects, measured in terms of successful bids for new acreage, increased success rate and volume delivery from exploration drilling, and more rapid progress in appraisal of discoveries. Describe concepts, simple processes, workflows and analysis tools for project execution. Tools include the expert course leader's proprietary project management framework, including project framing and after-action review methodologies, templates for strategy development, decision trees, decision quality frameworks. They also include customised Excel spreadsheets for portfolio modelling, project risk assessment (in new ventures and prospect maturation) and business planning. Understand their role in (a) delivering the company's strategy, (b) contributing data and assessments to key exploration decision makers, and (c) communicating project progress and results to senior management. Target Audience The Virtual Instructor Led Training (VILT) is aimed at exploration professionals with more than 5 to 10 years of experience in the business, who would like to develop their skills for managing exploration projects and presenting the goals and results of their project work to senior management. Exploration and engineering professionals who work in exploration project teams, across the spectrum from new ventures (exploration business development), prospect identification and maturation, and appraisal of discoveries Exploration project leaders Exploration managers The VILT will also benefit professionals from well engineering, petroleum engineering, finance and planning who support exploration activities. Participants are requested to bring a mini-poster (two PowerPoint slides, each printed on A3 paper) as background material for discussion during the course. Course Level Basic or Foundation Trainer Your expert course leader draws on more than 35 years of experience managing, reviewing and directing projects in all aspects of the exploration business: from exploration business development (new ventures), through prospect maturation and drilling, to the appraisal of discoveries. He has more than 30 years' experience with Shell International, followed by 10 years consulting to NOCs in Asia Pacific, Africa and South America and independent oil companies in the United Kingdom, continental Europe and North America. Other than delivering industry training, he has worked on projects for oil & gas companies of all sizes, including independents, national oil companies and (super)-majors, private equity firms, hedge funds and investment banks, and leading management consulting firms. He is an alumnus of Cambridge University. He has M.A and Ph.D. degrees in geology and is a Fellow of the Geological Society of London as well as a respected speaker on management panels at international conferences. Professional Experience Management consultancy & executive education: Advice to investment banks, businesses and major consulting firms. Specialist expertise in upstream oil & gas, with in depth experience in exploration strategy, portfolio valuation and risk assessment. Leadership: Managed and led teams and departments ranging from 3 - 60 in size. Provided technical leadership to a cadre of 800 explorationists in Shell worldwide. Member of the 12-person VP team leading global exploration in Shell, a $3 bln p.a. business and recognised as the most effective and successful among its industry peers. Accountability & decision-making: Accountable for bottom-line results: in a range of successful exploration ventures with budgets ranging from $10's million to $100's million. Made, or contributed to, complex business decisions / investments, taking into account strategic, technical, commercial, organisational and political considerations. Corporate governance: Served as non-executive director on the Boards of the South Rub al Khali Company (oversight of gas exploration studies and drilling in Saudi Arabia) and SEAPOS B.V. (exploration deep-water drilling and facilities management). Technical & operations: Skilled in exploration opportunity evaluation, the technical de risking of prospects, portfolio analysis and managing the interface between exploration and well engineering activities. Unparalleled knowledge of the oil and gas basins of the world, and of different operating regimes and contractual structures, ranging from Alaska, Gulf of Mexico and Brazil, through to the Middle East, former Soviet Union, Far East and Australia. Safety: Following an unsatisfactory audit, became accountable for safety performance in Shell's exploration new ventures. Through personal advocacy and leadership of a small team, delivered pragmatic and effective HSE systems, tools and staff training / engagement and a dramatically improved safety record. R&D: Experience in the 3 key roles in R&D: scientific researcher, research manager, and 'customer' for R&D products. After re-defining Shell's exploration R&D strategy, led the re-structuring of the R&D organization, its interface with 'the business' and approaches to deployment and commercialization. Strategy: Accomplished at formulating competitive strategies in business, R&D and technology deployment, translating them into actionable tactics and results. Defined the exploration strategy of PDO (a Shell subsidiary in Oman) and latterly of Shell's global exploration programme. Professional education, behavioural/motivational coaching: Experienced in organisational re-design, change management, leadership education and talent development. Commercial skills: Personally negotiated drilling compensation claims, educational contracts and E&P contracts, with values of $5 million to $100+ million. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations

Lean Six Sigma Black Belt Certification Program: In-House Training This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners. If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others. Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course. What you Will Learn At the end of this program, you will be able to: Use Minitab for advanced data analysis Develop appropriate sampling strategies Analyze differences between samples using Hypothesis Tests Apply Statistical Process Control to differentiate common cause and special cause variation Explain and apply various process capability metrics Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data Conduct and analyze simple and multiple regression analysis Plan, execute, and analyze designed experiments Drive sustainable change efforts through leadership, change management, and stakeholder management Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps Explain the main concepts of Design for Six Sigma including QFD Introduction: DMAIC Review IIL Black Belt Certification Requirements Review Project Selection Review Define Review Measure Review Analyze Review Improve Review Control Introduction: Minitab Tool Introduction to Minitab Minitab basic statistics and graphs Special features Overview of Minitab menus Introduction: Sampling The Central Limit Theorem Confidence Interval of the mean Sample size for continuous data (mean) Confidence Interval for proportions Sample size for discrete data (proportions) Sampling strategies (review) Appendix: CI and sample size for confidence levels other than 95% Hypothesis Testing: Introduction Why use advanced stat tools? What are hypothesis tests? The seven steps of hypothesis tests P value errors and hypothesis tests Hypothesis Testing: Tests for Averages 1 factor ANOVA and ANOM Main Effect Plots, Interaction Plots, and Multi-Vari Charts 2 factor ANOVA and ANOM Hypothesis Testing: Tests for Standard Deviations Testing for equal variance Testing for normality Choosing the right hypothesis test Hypothesis Testing: Chi Square and Other Hypothesis Test Chi-square test for 1 factor ANOM test for 1 factor Chi-square test for 2 factors Exercise hypothesis tests - shipping Non-parametric tests Analysis: Advanced Control Charts Review of Common Cause and Special Cause Variation Review of the Individuals Control Charts How to calculate Control Limits Four additional tests for Special Causes Control Limits after Process Change Discrete Data Control Charts Control Charts for Discrete Proportion Data Control Charts for Discrete Count Data Control Charts for High Volume Processes with Continuous Data Analysis: Non-Normal Data Test for normal distribution Box-Cox Transformation Box-Cox Transformation for Individuals Control Charts Analysis: Time Series Analysis Introduction to Time Series Analysis Decomposition Smoothing: Moving Average Smoothing: EWMA Analysis: Process Capability Process capability Discrete Data: Defect metrics Discrete Data: Yield metrics Process Capability for Continuous Data: Sigma Value Short- and long-term capabilities Cp, Cpk, Pp, Ppk capability indices Analysis: Measurement System Analysis What is Measurement System Analysis? What defines a good measurement system? Gage R&R Studies Attribute / Discrete Gage R&R Continuous Gage R&R Regression Analysis: Simple Correlation Correlation Coefficient Simple linear regression Checking the fit of the Regression Model Leverage and influence analysis Correlation and regression pitfalls Regression Analysis: Multiple Regression Analysis Introduction to Multiple Regression Multicollinearity Multiple Regression vs. Simple Linear Regression Regression Analysis: Multiple Regression Analysis with Discrete Xs Introduction Creating indicator variables Method 1: Going straight to the intercepts Method 2: Testing for differences in intercepts Logistic Regression: Logistic Regression Introduction to Logistic Regression Logistic Regression - Adding a Discrete X Design of Experiments: Introduction Design of Experiment OFAT experimentation Full factorial design Fractional factorial design DOE road map, hints, and suggestions Design of Experiments: Full Factorial Designs Creating 2k Full Factorial designs in Minitab Randomization Replicates and repetitions Analysis of results: Factorial plots Analysis of results: Factorial design Analysis of results: Fits and Residuals Analysis of results: Response Optimizer Analysis of results: Review Design of Experiments: Pragmatic Approaches Designs with no replication Fractional factorial designs Screening Design of Experiment Case Study Repair Time Blocking Closing: Organizational Change Management Organizational change management Assuring project sponsorship Emphasizing shared need for change Mobilizing stakeholder commitment Closing: Project Management for Lean Six Sigma Introduction to project management Project management for Lean Six Sigma The project baseline plan Work Breakdown Structure (WBS) Resource planning Project budget Project risk Project schedule Project executing Project monitoring and controlling and Closing Closing: Design for Lean Six Sigma Introduction to Design for Lean Six Sigma (DMADV) Introduction to Quality Function Deployment (QFD) Summary and Next Steps IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)

Lean Six Sigma Black Belt Certification Program This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners. If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others. Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course. What you Will Learn At the end of this program, you will be able to: Use Minitab for advanced data analysis Develop appropriate sampling strategies Analyze differences between samples using Hypothesis Tests Apply Statistical Process Control to differentiate common cause and special cause variation Explain and apply various process capability metrics Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data Conduct and analyze simple and multiple regression analysis Plan, execute, and analyze designed experiments Drive sustainable change efforts through leadership, change management, and stakeholder management Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps Explain the main concepts of Design for Six Sigma including QFD Introduction: DMAIC Review IIL Black Belt Certification Requirements Review Project Selection Review Define Review Measure Review Analyze Review Improve Review Control Introduction: Minitab Tool Introduction to Minitab Minitab basic statistics and graphs Special features Overview of Minitab menus Introduction: Sampling The Central Limit Theorem Confidence Interval of the mean Sample size for continuous data (mean) Confidence Interval for proportions Sample size for discrete data (proportions) Sampling strategies (review) Appendix: CI and sample size for confidence levels other than 95% Hypothesis Testing: Introduction Why use advanced stat tools? What are hypothesis tests? The seven steps of hypothesis tests P value errors and hypothesis tests Hypothesis Testing: Tests for Averages 1 factor ANOVA and ANOM Main Effect Plots, Interaction Plots, and Multi-Vari Charts 2 factor ANOVA and ANOM Hypothesis Testing: Tests for Standard Deviations Testing for equal variance Testing for normality Choosing the right hypothesis test Hypothesis Testing: Chi Square and Other Hypothesis Test Chi-square test for 1 factor ANOM test for 1 factor Chi-square test for 2 factors Exercise hypothesis tests - shipping Non-parametric tests Analysis: Advanced Control Charts Review of Common Cause and Special Cause Variation Review of the Individuals Control Charts How to calculate Control Limits Four additional tests for Special Causes Control Limits after Process Change Discrete Data Control Charts Control Charts for Discrete Proportion Data Control Charts for Discrete Count Data Control Charts for High Volume Processes with Continuous Data Analysis: Non-Normal Data Test for normal distribution Box-Cox Transformation Box-Cox Transformation for Individuals Control Charts Analysis: Time Series Analysis Introduction to Time Series Analysis Decomposition Smoothing: Moving Average Smoothing: EWMA Analysis: Process Capability Process capability Discrete Data: Defect metrics Discrete Data: Yield metrics Process Capability for Continuous Data: Sigma Value Short- and long-term capabilities Cp, Cpk, Pp, Ppk capability indices Analysis: Measurement System Analysis What is Measurement System Analysis? What defines a good measurement system? Gage R&R Studies Attribute / Discrete Gage R&R Continuous Gage R&R Regression Analysis: Simple Correlation Correlation Coefficient Simple linear regression Checking the fit of the Regression Model Leverage and influence analysis Correlation and regression pitfalls Regression Analysis: Multiple Regression Analysis Introduction to Multiple Regression Multicollinearity Multiple Regression vs. Simple Linear Regression Regression Analysis: Multiple Regression Analysis with Discrete Xs Introduction Creating indicator variables Method 1: Going straight to the intercepts Method 2: Testing for differences in intercepts Logistic Regression: Logistic Regression Introduction to Logistic Regression Logistic Regression - Adding a Discrete X Design of Experiments: Introduction Design of Experiment OFAT experimentation Full factorial design Fractional factorial design DOE road map, hints, and suggestions Design of Experiments: Full Factorial Designs Creating 2k Full Factorial designs in Minitab Randomization Replicates and repetitions Analysis of results: Factorial plots Analysis of results: Factorial design Analysis of results: Fits and Residuals Analysis of results: Response Optimizer Analysis of results: Review Design of Experiments: Pragmatic Approaches Designs with no replication Fractional factorial designs Screening Design of Experiment Case Study Repair Time Blocking Closing: Organizational Change Management Organizational change management Assuring project sponsorship Emphasizing shared need for change Mobilizing stakeholder commitment Closing: Project Management for Lean Six Sigma Introduction to project management Project management for Lean Six Sigma The project baseline plan Work Breakdown Structure (WBS) Resource planning Project budget Project risk Project schedule Project executing Project monitoring and controlling and Closing Closing: Design for Lean Six Sigma Introduction to Design for Lean Six Sigma (DMADV) Introduction to Quality Function Deployment (QFD) Summary and Next Steps IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)

Lean Six Sigma Green Belt Certification Program: In-House Training This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. Green Belt is not just a role, it is also a competency required for leadership positions at many top companies. This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. With a real-world project focus, the series will teach the fundamental methodology, tools, and techniques of the Define, Measure, Analyze, Improve and Control Process Improvement Methodology. This course is delivered through sixteen 3-hour online sessions. What you Will Learn At the end of this program, you will be able to: Identify strategies for effectively leading high performing process improvement teams Analyze whether projects align with business strategy Apply process improvement methodologies to DMAIC steps, based on real world scenarios Explain ways to appropriately respond to process variation Distinguish among best practice problem solving methodologies Evaluate and effectively communicate data-driven decisions, based on real world scenarios Introduction Lean Six Sigma & quality The vision The methodologies The metric Project Selection Why Projects Random idea generation Targeted idea generation CTQs (Critical to Quality) & projects Project screening criteria Quick improvements Introduction to Define Project Planning Developing the core charter Developing a project charter Facilitation Process Management Business process management Top-down process mapping Voice of the Customer Voice of Customer Stakeholder analysis Communication planning Kicking off the project Define Summary Introduction to Measure Data Collection Fact-based decision making Data sampling Operations definitions Data collection plan Measurement system analysis Graphical Statistics for Continuous Data Meet Six SigmaXL Graphical & statistical tools Data stratification Graphical Statistics for Discrete Data Pareto analysis Dot plots Plotting data over time: Looking for patterns Variation Concepts Variation is reality Special Cause and Common Cause variation Example of standard business reporting Individuals Control Chart Process Capability Genesis of process capability Calculating the metrics of Six Sigma Yield metrics: Measuring process efficiency Cost of Poor Quality The Cost of Poor Quality (COPQ) Cost of Quality categories Calculating the Cost of Poor Quality Measure Summary Introduction to Analyze Process Analysis Introduction to process analysis Value-added analysis Cycle time analysis WIP & pull systems Analyzing bottlenecks and constraints Cause & Effect Analysis Fishbone/Ishikawa diagram 5-Whys analysis Graphical & statistical tools Advanced Analysis Why use hypothesis rests? Hypothesis tests Correlation and regression analysis Analyze Summary Introduction to Improve Solutions Creativity techniques Generating alternative solutions Solution selection techniques Introduction to Design of Experiments Introduction to DOE DOE activity Error Proofing Failure mode & effect analysis Poka-Yoke Project Management Fundamentals Successful teams Project roles Conflict management Standardization Standardization The Visual Workplace 5S Piloting & Verifying Results What is a pilot? Evaluating results Improve Summary Introduction to Control Statistical Process Control Review of Special & Common Cause variation Review of Individual Control Chart P-Chart for discrete proportion data Transition Planning Control plan Project closure Control Summary Summary and Next Steps

Lean Six Sigma Green Belt Certification Program This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. Green Belt is not just a role, it is also a competency required for leadership positions at many top companies. This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. With a real-world project focus, the series will teach the fundamental methodology, tools, and techniques of the Define, Measure, Analyze, Improve and Control Process Improvement Methodology. This course is delivered through sixteen 3-hour online sessions. What you Will Learn At the end of this program, you will be able to: Identify strategies for effectively leading high performing process improvement teams Analyze whether projects align with business strategy Apply process improvement methodologies to DMAIC steps, based on real world scenarios Explain ways to appropriately respond to process variation Distinguish among best practice problem solving methodologies Evaluate and effectively communicate data-driven decisions, based on real world scenarios Introduction Lean Six Sigma & quality The vision The methodologies The metric Project Selection Why Projects Random idea generation Targeted idea generation CTQs (Critical to Quality) & projects Project screening criteria Quick improvements Introduction to Define Project Planning Developing the core charter Developing a project charter Facilitation Process Management Business process management Top-down process mapping Voice of the Customer Voice of Customer Stakeholder analysis Communication planning Kicking off the project Define Summary Introduction to Measure Data Collection Fact-based decision making Data sampling Operations definitions Data collection plan Measurement system analysis Graphical Statistics for Continuous Data Meet Six SigmaXL Graphical & statistical tools Data stratification Graphical Statistics for Discrete Data Pareto analysis Dot plots Plotting data over time: Looking for patterns Variation Concepts Variation is reality Special Cause and Common Cause variation Example of standard business reporting Individuals Control Chart Process Capability Genesis of process capability Calculating the metrics of Six Sigma Yield metrics: Measuring process efficiency Cost of Poor Quality The Cost of Poor Quality (COPQ) Cost of Quality categories Calculating the Cost of Poor Quality Measure Summary Introduction to Analyze Process Analysis Introduction to process analysis Value-added analysis Cycle time analysis WIP & pull systems Analyzing bottlenecks and constraints Cause & Effect Analysis Fishbone/Ishikawa diagram 5-Whys analysis Graphical & statistical tools Advanced Analysis Why use hypothesis rests? Hypothesis tests Correlation and regression analysis Analyze Summary Introduction to Improve Solutions Creativity techniques Generating alternative solutions Solution selection techniques Introduction to Design of Experiments Introduction to DOE DOE activity Error Proofing Failure mode & effect analysis Poka-Yoke Project Management Fundamentals Successful teams Project roles Conflict management Standardization Standardization The Visual Workplace 5S Piloting & Verifying Results What is a pilot? Evaluating results Improve Summary Introduction to Control Statistical Process Control Review of Special & Common Cause variation Review of Individual Control Chart P-Chart for discrete proportion data Transition Planning Control plan Project closure Control Summary Summary and Next Steps