Complex Project Management Training

Introducing complexity science and chaos theory

• Comparing and contrasting simple and complex systems
• Applying various complexity modelling techniques

Adopting the four-dimensional project complexity diagnostic tool

• Analysing project boundary conditions to understand the complexity of your project
• Determining the edge of chaos
• Assessing the significance of complex project risks
• Communicating project complexity factors to others

Beginning with adaptive principles

• Building with Agile software development
• Borrowing from the combat operations loop and the scientific method

The four-step adaptive project management process

• Implementing rolling wave planning and progressive elaboration
• Managing adaptive requirements, change and quality
• Scheduling, budgeting and metrics on complex projects

Aligning with corporate strategy and value engineering

• Executing portfolio management strategies
• Making the business case and delivering value
• Utilising business capability and purpose alignment models

Developing small, strategic batches of work

• Applying Van Creveld's Iron Rule and Occam's Razor
• Delivering minimal marketable features

Maintaining control through speed and agility

• Dealing with daily disruptions
• Employing fast-tracking and crashing
• Compressing the critical path

Incorporating Critical Chain and Lean techniques

• Evaluating Critical Chain project management
• Employing the theory of constraints and five focusing steps to eliminate waste and optimise flow

Leading adaptive teams

• Developing your core competencies
• Growing your sphere of influence and managing politics

Building CRACK teams

• Facilitating emergent organisation and self-management
• Agreeing on vision, goals, objectives and values
• Empowering and motivating the team
• Implementing effective feedback loops

Identifying and managing risks with scenario modelling

• Quantifying and mitigating risk threats
• Exploiting risk opportunities for disruptive innovation

Implementing probabilistic estimating tools and techniques

• Managing precision and accuracy
• Correcting estimating bias and reducing variability
• Revisiting the cone of uncertainty and order of magnitude estimating
• Leveraging PERT, Monte Carlo and Agile techniques

• Putting it all together
• Analysing a real-world case study
• Assessing your own real-world projects
• Identifying specific actions you will take
• Gaining support and managing risks