DESIGNING END-TO-END VALUE STREAMS: HOW GLOBAL PROCESS OWNERS ENABLE TRUE OPERATING MODEL TRANSFORMATION 

In most organizations, work still operates in functional silos. This session showcases the potential of shifting this model completely by enabling true horizontal ownership of key value streams by identifying critical end-to-end processes and empowering Global Process Owners (GPOs) with cross business decision rights.

• Why it’s transformation critical to shift from vertical, function-based execution to horizontal, end-to-end value streams 
• Standing up Global Process Owners (GPOs) to enable and govern end-to-end processes across business units 
• Walking through a blended methodology combining DMAC with a practical operating model “wheel” covering process, technology, data, talent, organization, performance, and governance 
• Identify how an end-to-end design enables higher value AI initiatives, and why process redesign must precede AI deployment 

LEVERAGE AI TO REINVENT AND TRANSFORM ENTERPRISE-WIDE VALUE CHAINS AND OPERATING MODELS 

Most organizations are “doing AI” through isolated pilots and task automation which result in limited productivity improvements. In this session, Rob shows how to move beyond cherry picking task-based use cases to redesigning entire value streams, providing tangible insights into how classic operational excellence tools like value stream analysis need to be re applied in the AI era to unlock cycle time, cost, and quality gains that actually show up in the P&L.

• Distinguish task-level AI productivity from true end to end value delivery 
• Use value stream analysis (processing vs. wait time) to prioritize AI investments 
• Accelerate AI discovery & design sprints grounded in OE principles 
• Design processes to adapt, scale and continuously evolve 
• Transform disjointed AI pilots into a coherent, enterprise-wide transformation narrative 

THE AI COST RECKONING: DISCIPLINED AI ADOPTION TO AVOID COST SPIRALS 

As AI moves beyond experimentation, transformation leaders face mounting pressure from CFOs to demonstrate clear, quantifiable ROI. Token consumption, bespoke multi agent architectures, and new infrastructure can cause costs to snowball before benefits materialize. Leaders need to weigh up their options carefully through hard numbers instead of getting caught in in the hype. Join this session to get a reality check on how leaders are tackling these key challenges including:

• How to best frame robust business cases for Agentic AI 
• When to involve finance and architecture teams 
• Decide when AI genuinely outperforms simply adding human capacity 
• Share real scenarios, lessons learned, and practical approaches to governing AI investments so that “doing AI” never eclipses creating measurable business value