Key Topics:

• Introduction to the Dynamic Process Transformation model
• Fundamentals of Process Excellence
• The shift from back-office to competitive advantage
• Understanding process maturity levels (Default, Intentional, Integrated, Responsive)
• Process excellence in the digital era
• Setting the stage: Efficiency vs. Effectiveness vs. Innovation

Learning Outcomes:

• Articulate the business case for dynamic process excellence
• Evaluate current process maturity within your organization
• Identify barriers to continuous process transformation

Key Topics:

• Operational excellence KPIs and benchmarks Metrics that drive both efficiency and effectiveness
• What can go wrong in operational excellence and how to address
• Model for operational excellence
• Building a transformation roadmap
• Securing stakeholder buy-in

Learning Outcomes:

• Develop a compelling business case for process excellence
• Select appropriate metrics to measure transformation progress
• Identify high-value process improvement opportunities

Key Topics:

• Moving beyond "monopolistic" process thinking
• Customer centricity in process design
• Understanding your process customers (users vs. stakeholders)
• Designing for customer experience, not just efficiency
• Human-centered process design
• Using Design Thinking for process innovation

Learning Outcomes:

• Design processes that balance standardization with customer needs
• Apply human-centered design principles to process challenges
• Develop feedback mechanisms that drive continuous improvement

Key Topics:

• Breaking down functional silos
• Applying product management principles to process excellence
• Creating a process service catalog
• Developing process value propositions
• Tools for end-to-end process ownership

Learning Outcomes:

• Structure teams for end-to-end accountability
• Apply product management techniques to process improvement
• Design governance models that balance control with agility

Key Topics:

• Designing your process operating model
• Creating transparency in costs, performance, and value
• Business-centric client engagement
• AI case studies and applications
• Process mining and digital enablement

Learning Outcomes:

• Build an operating model that delivers consistent results
• Implement transparency mechanisms that drive trust and improvement
• Evaluate and select appropriate technologies for process improvement

Key Topics:

• Understanding AI capabilities in process contexts
• Types of AI relevant to process excellence (ML, NLP, computer vision, etc.)
• Advanced AI concepts including agentic AI capabilities: Task orchestration and workflow automation, knowledge retention and continuous learning systems, Multi-system integration and collaboration
• AI readiness assessment for process organizations
• Data foundations for AI-enabled processes
• Ethics and governance in process AI
• Selecting the right use cases for AI in process excellence

Learning Outcomes:

• Assess organizational readiness for AI-enabled process transformation
• Identify high-value AI opportunities in process operations
• Design ethical and effective data foundations for AI initiatives
• Evaluate appropriate AI technologies for specific process challenges Implement transparency mechanisms that drive trust and improvement
• Evaluate and select appropriate technologies for process improvement

Key Topics:

• AI implementation roadmap for process excellence
• System architecture considerations: Integration points with existing systems, Human-in-the-loop design and oversight mechanisms, orchestration layer planning
• Implementation strategies: Process mining and analytics use cases, Intelligent automation beyond RPA, GenAI applications in process excellence
• Business service applications: Finance & accounting process optimization, HR service delivery enhancement, Procurement and supply chain optimization
• Integration with existing process frameworks: Embedding AI into workflow systems, Connecting with enterprise systems, Building hybrid human-AI process teams
• Measuring AI's impact on process performance: Productivity and efficiency metrics, Decision quality and cycle time, Cost reduction and value creation, Change management for AI adoption

Learning Outcomes:

• Create an implementation plan for AI-enabled processes
• Apply AI technologies to solve real-world process challenges
• Design appropriate metrics for AI-driven process excellence
• Integrate AI solutions with existing process frameworks
• Lead effective change management for AI-augmented processes

Key Topics:

• Change management and behavior & psychology
• Change management models for process excellence
• Creating followership and building momentum
• Managing by influence across organizational boundaries
• From project thinking to continuous transformation
• Organizational readiness assessment

Learning Outcomes:

• Apply change management principles to process initiatives
• Create organizational buy-in for process excellence initiatives
• Develop strategies to overcome resistance to change

Key Topics:

• Business-value obsessed process innovation (BOPI)
• Modern process excellence applications
• Combining Design Thinking, Lean Startup, and Agile methodologies
• Creating a culture of experimentation
• Building innovation capabilities at all levels
• Balancing efficiency with innovation

Learning Outcomes:

• Apply innovation methodologies to process challenges
• Create mechanisms for continuous process evolution
• Build organizational capabilities for sustained innovation

Key Topics:

• Integrating all framework elements into a cohesive approach
• Building organizational DNA for process excellence
• Measuring and communicating success
• Creating a movement for sustained transformation
• Developing your personal action plan
• Final certification assessment

Learning Outcomes:

• Develop an integrated approach to dynamic process excellence
• Create an implementation roadmap for your organization
• Articulate and measure the business impact of process excellence