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Salary
≈ $25k – $55k per year (Estimated)
Location
In office (Taipei)
Seniority
Staff · 10+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 21, 2026. First seen by Alion on Oct 21, 2026. HP Inc. scores A on the Alion truth index.

Overview
Company
Impact
Profile match
HP Inc. is an American technology company created in 2015 when the original Hewlett-Packard split its personal systems and printing businesses away from its enterprise arm. It is one of the largest personal computer vendors in the world, shipping consumer and commercial laptops, desktops and workstations under the HP, Pavilion, Envy, EliteBook, OMEN and Poly brands, alongside a printing division covering home, office, large-format and industrial 3D printing. Headquartered in Palo Alto, California, the company earns a large share of profit from supplies and services attached to its installed base and has pushed into hybrid-work peripherals and subscription hardware.
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 translate into sustained behavioral and operational change.

7. EXECUTIVE & CROSS-ORGANIZATIONAL LEADERSHIP

  • Consult with senior business leaders on strategic Commodity Planning issues, transformation priorities, risks and opportunities.
  • Act as a trusted advisor on planning transformation, analytics and emerging AI-enabled supply chain capabilities.
  • Communicate complex analytical, operational and technology topics clearly to both technical and non-technical stakeholders.
  • Influence stakeholders across organizational boundaries without necessarily having direct authority.
  • Lead alignment across business, analytics and technology organizations toward common transformation objectives.
  • Leverage industry and subject-matter expertise to contribute innovative principles and ideas to supply chain strategy and transformation.
  • Develop reusable frameworks, methodologies, tools and templates that strengthen broader Supply Chain transformation capabilities.

EDUCATION & EXPERIENCE

RECOMMENDED

  • Bachelor's or Master's degree in Supply Chain Management, Industrial Engineering, Operations Research, Business Analytics, Engineering, Operations Management, Business Administration or a related discipline, or equivalent demonstrated experience.
  • Typically 10+ years of relevant experience in supply chain planning, commodity/material planning, operations, analytics, transformation or related disciplines.
  • Strong experience with end-to-end supply chain planning processes, preferably including commodity/material planning, demand and supply balancing, inventory management and supply constraints.
  • Demonstrated experience leading large, complex and cross-functional transformation programs.
  • Experience developing and managing strategic roadmaps and prioritizing transformation portfolios.
  • Experience developing business cases, defining KPIs and quantifying business outcomes from transformation initiatives.
  • Demonstrated ability to structure ambiguous business problems and develop analytical and strategic approaches independently.
  • Proven ability to execute against strategy and navigate organizational complexity, ambiguity and competing priorities.
  • Strong executive communication, stakeholder management and influencing capabilities.

ANALYTICS & TECHNOLOGY

  • Strong analytical capability and demonstrated ability to use data to structure problems, evaluate alternatives and drive decisions.
  • Experience partnering with Data Science, Analytics, IT, engineering or other technical teams to deliver analytical or technology-enabled business capabilities.
  • Understanding of forecasting, predictive analytics, optimization, scenario analysis and statistical concepts.
  • Ability to interpret analytical and model outputs, challenge assumptions and translate findings into actionable business decisions.
  • Understanding of decision science principles, including trade-off analysis, uncertainty, constraints and scenario-based decision-making.
  • Working knowledge of analytical and visualization tools such as SQL, Power BI, Tableau or equivalent is preferred.
  • Familiarity with AI/ML applications in supply chain planning and decision support is strongly advantageous.
  • Experience with enterprise planning and supply chain technology platforms such as SAP, Kinaxis, o9, Blue Yonder or equivalent is advantageous.
  • Experience across ERP, master data, product data and related supply chain technology architecture is advantageous.
  • Python or other analytical programming experience is beneficial but not required.
  • Ability to work effectively with technical teams without requiring hands-on ownership of data engineering or model development.

PREFERRED EXPERIENCE

  • Experience within technology, electronics, semiconductor, manufacturing or other complex global supply chain environments.
  • Experience with commodity-level demand and supply planning, material constraints, component lifecycle management, allocation or supply-risk management.
  • Experience leading digital, analytics or AI-enabled supply chain transformation initiatives at regional or global scale.
  • Experience implementing scenario planning, optimization, demand sensing, predictive analytics or automated exception-management capabilities.
  • Experience driving process standardization, automation and adoption across large planning organizations.
  • Relevant professional certifications such as APICS CPIM/CSCP, PMP or equivalent are advantageous but not required.

KNOWLEDGE & SKILLS

  • Commodity and Supply Chain Planning
  • Supply Chain Transformation
  • Program and Portfolio Management
  • Business & Decision Analytics
  • Decision Science and Trade-off Analysis
  • Business Process Design
  • Advanced Analytics & AI
  • Scenario Planning
  • Inventory & Supply-Demand Management
  • Business Case Development
  • Financial & Value Analysis
  • Change Management & Adoption
  • Executive Stakeholder Management
  • Data & Digital Fluency
  • Structured Problem Solving
  • Risk Management
  • Strategic Roadmap Development

CROSS-ORGANIZATION SKILLS

  • Effective Communication
  • Results Orientation
  • Strategic Thinking
  • Learning Agility
  • Digital Fluency
  • Business Acumen
  • Stakeholder Management
  • Collaboration & Influence
  • Customer Centricity
  • Change Leadership

IMPACT & SCOPE

  • Impacts large supply chain functions and planning processes across multiple organizations.
  • Leads complex, cross-functional transformation programs involving business, analytics, technology and operational stakeholders.
  • Influences Commodity Planning strategy, process design, analytics adoption, technology priorities and investment decisions.
  • Owns or significantly influences a portfolio of transformation initiatives with material operational and financial impact.
  • Partners with senior leaders across Supply Chain, Transformation, Data Science & Analytics and Technology organizations.
  • Drives measurable business outcomes through improved planning decisions, analytics, automation and process transformation.

COMPLEXITY

  • Provides innovative solutions to complex and ambiguous supply chain planning problems.
  • Balances multiple and potentially competing objectives across inventory, material availability, cost, responsiveness, service and risk.
  • Operates across business, analytics and technology domains and translates between strategic objectives and executable capabilities.
  • Exercises significant independent judgment in structuring problems, prioritizing opportunities and driving cross-functional decisions.
  • Operates effectively where solutions, processes or requirements may not yet be fully defined.

ROLE PARTNERSHIP / OPERATING MODEL

The Principal Program Manager is the business-side owner and transformation lead for Commodity Planning initiatives and works in close partnership with Data Science & Analytics and other technical organizations.

Primary accountability includes:

  • Owning the business problem, business requirements and expected outcomes.
  • Defining planning processes, decision requirements, constraints and business rules.
  • Establishing transformation priorities and roadmap.
  • Leading business validation, readiness, implementation and adoption.
  • Tracking business performance and value realization.

Data Science & Analytics partners are primarily accountable for:

  • Analytical and technical solution design.
  • Data science methodology and model development.
  • Data engineering and analytical architecture.
  • Technical model validation and performance.
  • Technical deployment, monitoring and continuous model improvement.

Both organizations jointly ensure that analytical capabilities translate into effective, scalable and measurable improvements to Commodity Planning decisions.

DISCLAIMER

This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities or knowledge requirements. Responsibilities may evolve and additional functions may be assigned based on business needs.

Job -

Engineering

Schedule -

Full time

Shift -

No shift premium (Taiwan)

Travel -

Relocation -

Equal Opportunity Employer (EEO)-

HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).

Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.

For more information, review HP’sEEO Policy or read about your rights as an applicant under the law here: “ Know Your Rights: Workplace Discrimination is Illegal "

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