Source to Value Chain Process Engineer

Source to Pay Value Chain Process Engineer

The Value Chain Process Engineer – Source to Pay is responsible for shaping breakthrough transformation agendas by combining process excellence, digital capability, and industry benchmarking to define what "best in class" looks like. Acting as a trusted advisor to both business and digital leaders, the Value Chain Partner ensures that strategic investments and initiatives align to enterprise priorities, deliver measurable value, and advance HP's journey toward a process-led, digitally enabled organization.

Serving as a strategic architect of intelligent workflows, this role rethinks how Source to Pay (S2P) should operate in a process-led, AI-enabled enterprise. The Process Engineer partners with Global Process Owners, Digital, and Functional leaders to:

• Remove non-value-added steps
• Simplify complexity before layering automation
• Intentionally deploy AI where it enhances judgment, speed, and quality
• Explicitly define where AI should not be used
• This role ensures that transformation efforts produce structural simplification and measurable value.

Key Responsibilities

• Intelligent Workflow Redesign (AI as a Coworker)
• Redesign Source to Pay workflows assuming AI performs defined cognitive and transactional tasks alongside human operators.
• Define clear human-AI interaction models (decision rights, escalation paths, exception handling).
• Architect workflows where AI augments judgment, improves signal detection, and reduces manual coordination.
• Eliminate Before Automate
• Lead structured waste elimination across S2P (approvals, handoffs, reconciliations, rework, duplicate controls).
• Remove redundant steps before automation investment.
• Challenge legacy policies and controls that create unnecessary complexity.
• Ensure digital investment follows structural simplification.
• Simplify Before Layering Technology
• Standardize and harmonize S2P processes across business units before enabling AI or automation.
• Reduce process variation, exception pathways, and system fragmentation.
• Drive simplification of:
  • Requisition to PO workflows
  • Supplier onboarding and master data governance
  • Invoice matching and exception resolution
  • Payment controls and compliance checkpoints
• Intentional AI Deployment (and Non-Deployment)
• Evaluate when AI creates real value versus unnecessary complexity.
• Define criteria for:
  • Deterministic rule-based automation
  • AI-assisted decisioning
  • Human-only decision authority
• Ensure AI usage aligns with risk, compliance, and ethical standards in procurement and finance.
• Avoid "AI for AI's sake" solutions.
• Deep Source to Pay Expertise
• Own process redesign across:
  • Supplier Strategy & Selection
  • Contract Lifecycle Integration
  • Requisition to Purchase Order
  • Invoice to Pay
  • Supplier Performance & Risk Management
• Embed compliance, control integrity, and auditability into redesigned workflows. Partner with Finance, Risk, and Legal to ensure transformation strengthens control posture.
• Strategic Partnership & Governance
• Partner with Global Process Owners to redefine best-in-class S2P maturity in an AI-enabled enterprise.
• Shape digital investment priorities based on structural impact, not tool capabilities.
• Participate in governance forums to ensure alignment to enterprise architecture and value realization.
• Value Realization & Measurable Impact
• Define leading and lagging indicators for S2P transformation:
  • Cycle time reduction
  • Touchless transaction rates
  • Exception rate reduction
  • Supplier satisfaction
  • Working capital impact
  • Partner with Finance and PMO to validate measurable outcomes.

Qualifications

Education

Bachelor's degree required; MBA or advanced degree preferred.

Experience

• 10+ years in leading Supply Chain, Procurement, Finance Operations, or Digital Transformation organizations.
• Deep hands-on experience in Source to Pay transformation.
• Proven experience redesigning workflows.
• Experience implementing automation, AI/ML, analytics, or ERP platforms in enterprise environments.
• Demonstrated ability to simplify complex cross-functional processes.

Core Capabilities

• Workflow architecture thinking (systems over silos)
• Lean mindset (eliminate waste before digitizing)
• AI literacy (understanding model strengths, limits, and risks)
• Strong…