Global Head of Customer Experience
Listed on 2026-03-05
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IT/Tech
Data Analyst, Data Science Manager, Data Security, Business Systems/ Tech Analyst
Job Description Summary
Lead GE Health Care’s Global Customer Experience organization with a focus on standardizing digitizing, and continuously improving the end‑to‑end order to cash (O2C) lifecycle—from order intake through installation, customer acceptance, and revenue recognition. This leader will set global standards, deploy AI‑enabled processes, and drive cultural transformation across regions and business units to deliver best‑in‑industry customer experience, operational agility, and cash velocity.
Success requires deep mastery of order operations and supply chain process management, exceptional change leadership in a matrixed, change‑resistant environment, and a demonstrated passion for people development, engagement, and bench strength.
- Global scale: 170+ countries served; multi‑billion‑dollar revenue flow and backlog exposure.
- Value chain span:
Order capture (CRM/CPQ), order management (ERP/OMS), configuration & change control, date management (CSD/OTD), logistics, installation, customer acceptance, revenue recognition, and residuals closure. - Technology ecosystem: ERP (e.g., SAP), CRM (e.g., Salesforce), service and case platforms, analytics/BI, AI/ML and automation (incl. agent‑assist and agentic AI).
- Operating model:
Enterprise Center of Excellence (CoE) with global deployment, governance and continuous improvement.
- Strategy, Standards & Governance
- Define a multi‑year Customer Experience strategy and blueprint for a unified, scalable O2C operating model across regions and segments.
- Establish and govern global standards (SOPs, process controls, RACIs) for order intake, configuration/change management, date stability, fulfillment, installation, customer acceptance, and revenue recognition.
- Build and chair enterprise governance for O2C performance, including policy, exception handling, and risk controls (revenue, regulatory, privacy).
- Lead change management at scale—shifting mindsets from reactive support to proactive, data‑ and AI‑driven customer success.
- Digital, AI & End‑to‑End Connectivity
- Architect an integrated, AI‑enabled customer and employee experience:
- End‑to‑end journey mapping integrated with CRM, ERP/OMS, field/service platforms, and analytics to create a unified customer view.
- Self‑service & virtual care: AI chat, knowledge automation, and sentiment/intent to deliver 24/7, personalized and proactive support.
- Agent‑assist & agentic AI to improve productivity, accuracy, and cycle times for complex orders and escalations.
- Define AI governance (model oversight, accuracy, bias, security, auditability) with DT/IT, Data, Legal, and Compliance.
- Operational Excellence & Performance Management
- Set and manage KPIs/OKRs across the O2C value stream, including:
- Customer: CSAT, NPS, First‑Contact Resolution (FCR), time‑to‑resolution.
- Operations:
Order accuracy, change‑order velocity, COSD date stability / OTD, installation cycle time, backlog health, residuals closure. - Financial:
Revenue recognition timeliness, cash acceleration (DSO), cost‑to‑serve, automation rate. - Drive Lean/Six Sigma continuous improvement, eliminating bottlenecks and waste while scaling digital/automation.
- Partner with Product, Engineering/DT, Data/Analytics, Supply Chain, Logistics, Service/Installation, and Finance to embed process and data integrity into platforms and releases.
- Customer Journey, Installation & Acceptance
- Ensure seamless execution from order through installation and customer acceptance, including regulatory, radiation safety, civil works readiness, and site enablement.
- Industrialize standard work for change orders, configuration deviations, and escalations with Supply Chain & Logistics to protect dates and accuracy.
- Strengthen turnkey and hybrid delivery models; set clear readiness criteria and educate customers on realistic timelines.
- Leadership, Talent & Culture
- Build and lead a high‑performing global CoE (CX design, order operations, data/analytics, AI/automation, Lean).
- Model a culture of transparency, accountability, experimentation, and continuous learning.
- Invest in leadership pipelines, role clarity (e.g., AM/PJM/PMI interfaces), and capability uplift; achieve low attrition and…
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