763 Courses in London

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 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)

Management of Value (MoV®) Practitioner This interactive MoV® Practitioner course provides a modular and case-study-driven approach to learning Management of Value (MoV). The core knowledge is structured and comprehensive; and well-rounded modules cover the methodology and various techniques. A case study is used to help appreciate the relevance of MoV in its practical application. What you will Learn The MoV Practitioner Course prepares you for the MoV Practitioner exam. Individuals certified at the MoV Practitioner level will be able to: Apply Management of Value (MoV) principles, processes and techniques, and advocate the benefits of this application appropriately to the senior Management. Develop a plan of MoV activities for the whole lifecycle of small and large projects and programs. Plan an MoV study, tailoring it to particular projects or programs and developing practical study or workshop handbooks as required. Understand and articulate value in relation to organizational objectives. Prioritize value drivers using function analysis and use these to demonstrate how value might be improved. Quantify monetary and non-monetary value using the Value Index, Value Metrics and the Value for Money ratio. Describe and comment on the application of various techniques relevant to MoV. Monitor improvements in value realized throughout a project lifecycle and capture learning which can be transferred to future projects. Offer suggestions and guidance about embedding MoV into an organization, including policy issues, undertake a health check, assess maturity and competence, and provide guidance on typical roles and responsibilities. Understand and articulate the use of MoV within other Best Management Practice methods and its contributions to them Benefits of Taking This Course Upon successful completion of this course, you will be able to: Organise and contribute constructively to a Management of Value (MoV) Study Demonstrate a knowledge of MoV principles, processes, approach, and environment Analyse a company, programme or project to establish its organisational value includes identification and weighting of Value Drivers Pass the AXELOS Practitioner Examination Function Analysis Customer FAST Diagram Value Tree Development Weighting Attributes Paired Comparisons Developing a Value Profile Developing a Value Index Value for Money Ratio Stimulating Innovation Value Engineering Option Evaluation and Selection Evaluation Matrix Value and Value for Money Timing and Planning Teams and Stakeholders MoV in the Organization Integrating with Best Management Practice Relationship between Process and Approach

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

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

Scrum Master and Product Owner Workshop This workshop builds on the specific roles and responsibilities of the Product Owner and Scrum Master in a Scrum environment, and how they need to work together as part of the Scrum methodology. During these sessions, you will explore who does what before, during, and after the Scrum Sprint cycles, as well as how to make the process work best in your specific Agile environment. You will come away from this workshop with a much deeper understanding of the roles and responsibilities so that individual performance improves on the job. Improved target results include providing focused leadership, making effective decisions, guiding Agile teams, and delivering business value. Foundation Concepts Agile History, Values, and Mindset Introduction to Scrum Scrum Events Scrum Artifacts Scrum Roles and Responsibilities Scrum Roles Product Owner Responsibilities Scrum Master Responsibilities The Scrum Team Responsibilities Cross-functional Teams Product Ownership Product Ownership Vision Understand Your Customers and Market Stakeholder Management and Engagement Product Backlog What is a User Story? Epics and User Stories Acceptance Criteria Preparing User Stories for a Sprint Definition of Ready (DoR) and Definition of Done (DoD) User Story Estimation Using Planning Poker Backlog Grooming Roadmaps, Story Maps, Impact Mapping Product Backlog Prioritization, MoSCoW, Kano Analysis Technical Debt The Sprint Team Capacity and Velocity Planning Sprint Planning Meeting and Sprint Plan The Sprint: Learning to Become Self-managing, Self-organizing, Self-improving Sprint Review Meeting Retrospectives Project Progress and Completion The Daily Scrum The Task Board and The Burndown Chart Information Radiators Closing a Scrum Project Summary and Next Steps Review of course goals, objectives, and content

Scrum Master and Product Owner Workshop This workshop builds on the specific roles and responsibilities of the Product Owner and Scrum Master in a Scrum environment, and how they need to work together as part of the Scrum methodology. During these sessions, you will explore who does what before, during, and after the Scrum Sprint cycles, as well as how to make the process work best in your specific Agile environment. You will come away from this workshop with a much deeper understanding of the roles and responsibilities so that individual performance improves on the job. Improved target results include providing focused leadership, making effective decisions, guiding Agile teams, and delivering business value. Foundation Concepts Agile History, Values, and Mindset Introduction to Scrum Scrum Events Scrum Artifacts Scrum Roles and Responsibilities Scrum Roles Product Owner Responsibilities Scrum Master Responsibilities The Scrum Team Responsibilities Cross-functional Teams Product Ownership Product Ownership Vision Understand Your Customers and Market Stakeholder Management and Engagement Product Backlog What is a User Story? Epics and User Stories Acceptance Criteria Preparing User Stories for a Sprint Definition of Ready (DoR) and Definition of Done (DoD) User Story Estimation Using Planning Poker Backlog Grooming Roadmaps, Story Maps, Impact Mapping Product Backlog Prioritization, MoSCoW, Kano Analysis Technical Debt The Sprint Team Capacity and Velocity Planning Sprint Planning Meeting and Sprint Plan The Sprint: Learning to Become Self-managing, Self-organizing, Self-improving Sprint Review Meeting Retrospectives Project Progress and Completion The Daily Scrum The Task Board and The Burndown Chart Information Radiators Closing a Scrum Project Summary and Next Steps Review of course goals, objectives, and content

Virtual Agile Teams Agile teams are a must in this world of intense competition, marketing demands, and changing expectations. Global virtual teaming has become a necessity as organizations become increasingly distributed, with suppliers and clients actively engaged in joint projects. Agile Teams now work across geographical, organizational, and cultural boundaries to deliver solutions and services to global users. Distance and differences may amplify the effect of issues and factors that are relatively straightforward for co-located Agile teams. This workshop delivers practical concepts and techniques that participants will start using immediately with their virtual Agile teams. The goal of the course is to enable you to successfully execute your preferred Agile or Scrum methods in a virtual project team environment. What you will Learn At the end of this program, you will be able to: Explain the characteristics of a virtual team and how they differ from a co-located team Build an effective virtual Agile team using a Team Charter approach Develop Release Plans, including prioritizing user stories, with a virtual Agile Team Construct a Sprint plan, including effective user story estimates, virtually Execute a Sprint, including essential Agile or Scrum ceremonies, virtually Conduct effective virtual meetings in an environment supportive of Agile and Scrum methods Foundation Concepts Agile Mindset and Values Agile Benefits and Methods Scrum Overview Co-located vs. Virtual Teams Forming Virtual Agile Teams Exploring Virtual Leadership Focusing on Virtual Agile Leaders Developing a Virtual Agile Team Charter Meeting Team Challenges in a Virtual Environment Planning Releases with a Virtual Agile Team Planning releases overview Estimating user stories Prioritizing user stories Setting release parameters Getting consensus on the release plan Planning a Sprint for a Virtual Project Sprint Planning Overview Confirming Sprint Scope with Virtual Agile Teams Developing a Sprint Delivery Plan for Virtual Agile Teams Running a Sprint in a Virtual Environment Self-organizing a Sprint for a Virtual Agile Team Using Scrum tools in a Virtual Environment Conducting End of Sprint Meetings in a Virtual Environment Iterating as a Virtual Agile Team Creating an Environment for Success Piloting a virtual Agile team Creating an Agile-friendly virtual environment

Virtual Agile Teams: In-House Training Agile teams are a must in this world of intense competition, marketing demands, and changing expectations. Global virtual teaming has become a necessity as organizations become increasingly distributed, with suppliers and clients actively engaged in joint projects. Agile Teams now work across geographical, organizational, and cultural boundaries to deliver solutions and services to global users. Distance and differences may amplify the effect of issues and factors that are relatively straightforward for co-located Agile teams. This workshop delivers practical concepts and techniques that participants will start using immediately with their virtual Agile teams. The goal of the course is to enable you to successfully execute your preferred Agile or Scrum methods in a virtual project team environment. What you will Learn At the end of this program, you will be able to: Explain the characteristics of a virtual team and how they differ from a co-located team Build an effective virtual Agile team using a Team Charter approach Develop Release Plans, including prioritizing user stories, with a virtual Agile Team Construct a Sprint plan, including effective user story estimates, virtually Execute a Sprint, including essential Agile or Scrum ceremonies, virtually Conduct effective virtual meetings in an environment supportive of Agile and Scrum methods Foundation Concepts Agile Mindset and Values Agile Benefits and Methods Scrum Overview Co-located vs. Virtual Teams Forming Virtual Agile Teams Exploring Virtual Leadership Focusing on Virtual Agile Leaders Developing a Virtual Agile Team Charter Meeting Team Challenges in a Virtual Environment Planning Releases with a Virtual Agile Team Planning releases overview Estimating user stories Prioritizing user stories Setting release parameters Getting consensus on the release plan Planning a Sprint for a Virtual Project Sprint Planning Overview Confirming Sprint Scope with Virtual Agile Teams Developing a Sprint Delivery Plan for Virtual Agile Teams Running a Sprint in a Virtual Environment Self-organizing a Sprint for a Virtual Agile Team Using Scrum tools in a Virtual Environment Conducting End of Sprint Meetings in a Virtual Environment Iterating as a Virtual Agile Team Creating an Environment for Success Piloting a virtual Agile team Creating an Agile-friendly virtual environment

About this Training Course Liquefied Natural Gas (LNG) has provided intercontinental mobility to natural gas, which now provides about 25% of the global primary energy. Being the cleanest fossil fuel, natural gas/LNG consumption is forecasted to grow in all future scenarios. With the entry of various players, including Trading companies, the LNG value chain is becoming increasingly complex, and a solid understanding of its economics and management of its interfaces have become crucial to identify and assess investment opportunities and risks. Recent market disturbances caused by COVID-19, Oil & Gas price instabilities - coupled with the political (Ukraine/Russia) challenges - make a deep understanding of LNG Value Chain Logistics and Economics even more essential to ensure the security of energy supplies sustainably and profitably. This intermediate level 3 full-day course starts with a concise introduction to the LNG business. Thereafter, the elements of the LNG value chain are described, and their individual economics analysed. A Business Activity Model along the value chain will be developed and discussed in depth, covering the following key processes: 'Buy Gas - Transport Gas - Liquefy Gas - Sell LNG/Products - Ship LNG - Regasify LNG' The integrated chain economics will then be developed and quantified. A hands-on group workshop/exercise developing the economic case of a full-sized Liquefaction project will be carried out, considering the forecasted cash flows throughout the project life, the location of the plant, its markets, project sensitivities and profitability assessment. Participants will be provided with Excel based tools/models (LNG Liquefaction project development Net Present Value (NPV) analyses, Shipping Freight Calculations and Economics) to work through the exercises and also for their future personal use. Training Objectives After the completion of this course, participants will be able to: Understand how the LNG Value Chain operates, bound by the relevant Contracts and Agreements. Learn the basic economic parameters (operating, capital costs, financing, profitability) of each major element of the value chain. Appreciate the complexity of the value chain, and the associated opportunities and risks. Develop quantitative project evaluation skills. Explore options to maximise profitability in a given LNG value chain. Discuss best practices on how to manage, steer and govern these activities. Target Audience Technical, Operational, Shipping, Commercial, Project and Governance professionals who are already active in a specific section of the LNG Value Chain will directly benefit in developing a wider and deeper perspective on how the LNG Value Chain operations and can be optimised. Managers (Technical, Financial, Legal and Governance) less familiar with the specifics of the LNG Industry will also benefit from attending this VILT course, as they will obtain the required background to be able to set sharper targets, suitable performance indicators, and governance and performance assessment guidelines for units engaged in the chain. The course is most relevant for professionals engaged in the LNG industry at: National and International Oil & Gas/Energy Companies LNG Importers/Exporters/Traders/Shippers Government & Regulatory Agencies Finance Institutions It will also apply to the following audience: Business Development Managers Corporate Planning Professionals Project Developers Supply Planners & Scheduling Professionals Regulators Tax & Finance Advisors Compliance Officers Equity Analyst and Bankers Joint Venture Representatives, Board Directors Negotiators and Contracting Staff Trading Professionals Course Level Intermediate Trainer Your expert course leader is an Oil & Gas/LNG professional with more than 35 years of international experience, majority of which was gained at Shell International Joint Ventures engaged in Oil Refining, Supply / Trading, Gas Supply and LNG Businesses in the Netherlands, France, Thailand, Dominican Republic and Nigeria. Since 2004, he has had several roles in the management of the LNG Value Chain including the Commercial Operational Management of Nigeria LNG (NLNG). He played an active role in the start-up and integration of LNG trains 4, 5 and 6 with NLNG becoming the 3rd largest LNG producer in the world in 2007. Commercial operations spanned 4 Gas Supply, 11 LNG Sales & Purchase Agreements, ad-hoc LPG and Condensate Sales and LNG Ship Chartering contracts. Under his supervision, more than 2,000 LNG cargoes were exported. He was part of the organizational transformation of the company from a Project-based set-up to a Production / Commercial based structure and implemented an 'Integrated Planning and Scheduling Department' in which he optimized the value chain (Buy-Gas - Liquify Gas to LNG - Sell - Ship LNG). Staff competence management was one of his focus areas during this period. He was also the NLNG representative on JV Technical, Commercial, Shipping Committees where he interfaced with Government & Regulatory authorities. In 2014, he was appointed as Shell Shareholder representative to NLNG and became a Non-Executive Board member to NLNG companies, including Bonny Gas Transport (BGT) managing 24 LNG Ships. During this period, he was involved in the Economic and Technical steering of the Shipping Fleet and Liquefaction Plant Rejuvenation projects and a further capacity expansion of liquefaction plant which resulted in the achievement of NLNG train 7 project FID in 2019. Since 2016, he has been active as an independent consultant. He co-authored 2 patents and more than 30 published papers/presentations. He holds a PhD from Delft University of Technology in the Netherlands and a MSc and BSc in Chemical Engineering from the University of Birmingham, UK. 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 post training support and fees applicable Accreditions And Affliations