Program Manager, Supply Chain Commodity Planning, Analytics & Transformation

Program Manager, Supply Chain Commodity Planning, Analytics & Transformation

Description -

JOB SUMMARY

HP is seeking a highly experienced Program Manager, Supply Chain Commodity Planning, Analytics & Transformation to lead strategic transformation across Supply Chain Commodity Planning through advanced analytics, automation, process redesign and AI-enabled decision capabilities.

This role will serve as a senior business leader and key interface between Commodity Planning, Supply Chain Transformation, and Data Science & Analytics teams, translating complex planning challenges into scalable business processes, analytical capabilities and decision solutions.

The Principal Program Manager will independently define transformation strategies, own and evolve the Commodity Planning transformation roadmap, identify and prioritize high-value opportunities, and lead complex cross-functional programs from problem definition through implementation, adoption and value realization.

The role requires deep supply chain planning expertise combined with structured problem solving, decision science, program leadership and technology fluency. The successful candidate will be expected to challenge existing planning practices, evaluate trade-offs across inventory, material availability, cost, responsiveness and risk, and influence senior stakeholders toward improved planning decisions and operating models.

The role will partner closely with Data Science & Analytics teams on capabilities including predictive analytics, demand sensing, inventory optimization, scenario planning, exception management and AI-enabled planning, while maintaining clear business ownership of requirements, process design, adoption and business outcomes.

RESPONSIBILITIES

1. COMMODITY PLANNING & BUSINESS PROCESS LEADERSHIP

Develop deep understanding of end-to-end Commodity Planning processes, business decisions, constraints and performance drivers across demand, supply, inventory and material availability.

Identify planning inefficiencies, decision gaps and opportunities for process transformation, advanced analytics, automation and AI-enabled decision support.

Translate complex business challenges into clearly structured problem statements, use cases, business requirements and measurable outcomes.

Define and evaluate planning trade-offs across inventory, material availability, cost, service, responsiveness and supply risk.

Partner with commodity planners and cross-functional stakeholders to define decision rules, business constraints, exception-management approaches and operational requirements.

Challenge existing planning practices and operating models where opportunities exist to simplify, standardize, automate or improve decision quality.

2. ANALYTICS, AI & DECISION-SUPPORT TRANSFORMATION

Act as a primary business partner to Data Science, Analytics and technical teams in the development and deployment of advanced planning capabilities.

Translate business problems and planning decisions into analytical requirements, decision frameworks, success criteria and expected business outcomes.

Partner on initiatives including predictive analytics, demand sensing, inventory optimization, scenario planning, exception management and AI-enabled planning.

Evaluate analytical outputs and model recommendations for business relevance, operational feasibility and decision-making effectiveness.

Lead business validation and user acceptance of analytical solutions, ensuring capabilities solve the intended planning problem rather than simply meeting technical specifications.

Identify opportunities to automate low-risk planning decisions while establishing appropriate exception, override and governance mechanisms.

Promote effective use of analytics and AI while maintaining appropriate human decision-making, controls and business accountability.

Partner with Data Science & Analytics teams to continuously improve analytical capabilities based on business performance, user feedback and evolving planning requirements.

3. STRATEGY, ROADMAP & PORTFOLIO LEADERSHIP

Own and continuously evolve the Commodity Planning transformation roadmap and portfolio, establishing priorities based on business value, strategic alignment, analytical opportunity, implementation feasibility and organizational readiness.

Align the roadmap with broader Supply Chain Transformation priorities, business strategy and go-forward process and technology architecture.

Independently structure analytical approaches and develop project strategies using advanced supply chain and industry knowledge.

Identify, assess and prioritize transformation opportunities across planning processes, systems, analytics and automation.

Establish clear sequencing, dependencies and investment priorities across transformation initiatives.

Provide strategic recommendations to senior leadership on planning transformation priorities, opportunities, risks and investment decisions.

Leverage industry and subject-matter expertise to introduce innovative approaches, frameworks and leading practices into Commodity Planning.

4. PROGRAM & CROSS-FUNCTIONAL LEADERSHIP

Lead complex, large-scale and cross-functional transformation programs from problem definition and planning through execution, implementation and stabilization.

Establish project scope, milestones, deliverables, dependencies, risks, governance and stakeholder responsibilities.

Coordinate across Commodity Planning, Supply Chain Transformation, Data Science & Analytics, IT and other business and technical stakeholders.

Drive prioritization and decision-making across competing business requirements and organizational priorities.

Proactively identify program risks, dependencies and barriers, and drive appropriate mitigation and resolution.

Navigate organizational complexity and ambiguity while maintaining execution momentum and accountability.

Provide leadership, mentoring and guidance to cross-functional project teams to achieve program objectives.

Ensure transformation initiatives remain aligned with intended business outcomes throughout execution and avoid unnecessary scope or solution drift.

5. BUSINESS CASE, PERFORMANCE & VALUE REALIZATION

Conduct investigations and develop business cases and financial analyses for supply chain transformation and analytics initiatives.

Define measurable success criteria, baseline performance and KPIs before implementation.

Use benchmarking, statistical analysis and business performance data to identify improvement opportunities and develop new processes, strategies and capabilities.

Monitor relevant planning performance dimensions including forecast performance, inventory, material availability, supply risk, planning productivity and exception resolution.

Quantify and track realized business benefits following implementation.

Evaluate whether implemented capabilities are delivering expected operational and financial outcomes and initiate corrective actions where required.

Use performance insights to identify additional opportunities for continuous improvement and future roadmap development.

6. CHANGE MANAGEMENT & BUSINESS ADOPTION

Own business readiness and adoption of new planning processes, analytical capabilities and tools.

Develop implementation strategies that integrate new capabilities into existing planning workflows and decision processes.

Lead business validation, user acceptance testing, process documentation, training and change-management activities.

Establish sustainable operating models, governance, controls and accountability for analytics-enabled planning.

Gather user feedback and work with technical teams to continuously improve deployed capabilities.

Drive high adoption by ensuring solutions are relevant, intuitive and demonstrably improve planning effectiveness.

Define and monitor adoption metrics to ensure transformation initiatives t