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Course Outline
Overview of Process Thinking and a Culture of Improvement
- Viewing operational workflows as mechanisms for delivering value.
- Assessing the financial impact of quality defects and latent operational inefficiencies.
- Reviewing the continuous improvement framework and the Plan-Do-Check-Act (PDCA) methodology.
- Defining responsibilities for leadership, process ownership, and team participation in improvement initiatives.
Foundations of Business Process Model and Notation (BPMN) 2.0
- Exploring core BPMN components, including events, activities, gateways, and sequence flows.
- Utilizing pools, lanes, and message flows to map cross-functional operational interactions.
- Documenting existing operational procedures (as-is) based on actual execution data.
- Identifying common modeling errors and implementing best practices to ensure accuracy.
Introduction to Six Sigma Methodology and the DMAIC Framework
- Adopting a Six Sigma approach focused on minimizing variation and eliminating defects.
- Reviewing the DMAIC cycle: Define, Measure, Analyze, Improve, and Control.
- Establishing criteria for selecting projects based on scope and organizational priority.
- Formulating project charters with clearly defined, measurable objectives.
Define Phase: Clarifying Problems and Process Scope
- Converting operational challenges into precise, actionable problem statements.
- Applying techniques to capture Voice of the Customer (VOC) and Voice of the Business (VOB) requirements.
- Developing SIPOC diagrams to establish clear boundaries for the process under review.
- Setting Specific, Measurable, Achievable, Relevant, and Time-bound (SMART) goals for improvement efforts.
Measure Phase: Data Collection and Performance Baselines
- Identifying critical performance indicators such as cycle time, lead time, error rates, and throughput.
- Planning data collection strategies to determine what to measure, the methodology, and data sources.
- Establishing current performance baselines using run charts and histograms.
- Conducting measurement system analysis to ensure data integrity and reliability.
Analyze Phase: Identifying Root Causes
- Conducting process analysis through value stream mapping and identification of bottlenecks.
- Utilizing root cause analysis tools, including the 5 Whys, Ishikawa (fishbone) diagrams, and Pareto analysis.
- Applying fundamental statistical concepts such as mean, standard deviation, and process capability.
- Validating identified root causes using empirical data and evidence.
Process Analysis and Future-State Design Using BPMN
- Evaluating as-is models for redundancies, unnecessary handoffs, and decision points causing delays.
- Modeling the optimized future state (to-be) with streamlined operational flows.
- Incorporating gateways and events to represent exception handling and escalation paths.
- Aligning process redesign efforts with recommendations derived from the DMAIC analysis.
Improve Phase: Developing and Implementing Solutions
- Generating improvement strategies through structured brainstorming sessions.
- Assessing and prioritizing solutions using impact-effort matrices.
- Piloting changes through small-scale experiments and identifying quick wins.
- Managing process changes through clear communication, staff training, and phased rollouts.
Control Phase: Maintaining Achieved Gains
- Developing standard operating procedures (SOPs) based on the improved processes.
- Implementing control plans that monitor key metrics and establish control limits.
- Creating visual management dashboards for ongoing performance tracking.
- Establishing response protocols for instances where metrics deviate from control limits.
Statistical Process Control and Advanced Monitoring Techniques
- Introducing control charts, including X-bar, R-charts, and p-charts.
- Interpreting control chart signals to distinguish special cause variation from common cause.
- Using spreadsheet tools or basic software to build and maintain control charts.
- Integrating statistical monitoring into routine management activities.
Process Automation and Technology Enablers
- Connecting BPMN models to workflow automation and digital process management tools.
- Evaluating low-code and no-code platforms for automating repetitive tasks.
- Integrating Six Sigma initiatives with Enterprise Resource Planning (ERP) and inventory systems.
- Developing a business case to support technology investments.
Cultivating a Continuous Improvement Culture
- Incorporating regular process reviews into team operational rhythms.
- Training staff and scaling process improvement practices across departments.
- Managing knowledge by maintaining process repositories and documenting lessons learned.
- Developing internal champions to sustain momentum and accountability after training.
Requirements
- A basic understanding of business operations and daily workflows
- Familiarity with the organization's processes and departmental roles
- No prior technical or statistical background is required
Audience
- Process Department personnel and operations team members
- Team leaders and supervisors responsible for workflow optimization
- Professionals seeking practical tools to challenge the status quo and drive continuous improvement
21 Hours
Testimonials (4)
a multitude of points
Joanna - Instytut Ekonomiki Rolnictwa i Gospodarki Zywnosciowej-PIB
Course - Statistical Analysis with Stata and R
knowledge of the trainer, tailor based, all topics covered
eleni - EUAA
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The variation with exercise and showing.
Ida Sjoberg - Swedish National Debt Office
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The real life applications using Statcan and CER as examples.
