Director, Modality Excellence – Indirect Processes, Quality, Engineering & Maintenance, and Warehouse

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Job Description

About the role:

As Director, Modality Excellence, you will define, codify and deploy global excellence standards for indirect and enabling processes that influence manufacturing performance, quality flow, cost, capacity, service and reliability.

Based in a manufacturing or hub site, you will join GSQ’s Transformation Office and report to the Head of Value Stream Transformation. As a senior individual contributor and global process authority, you will work across Site Leadership, Quality, Engineering, Maintenance, Warehouse, Supply Chain, Finance, Manufacturing Science, Digital and Transformation Office teams.

Your scope will cover indirect processes and Quality operations—including deviations, CAPA, change controls, investigations, documentation workflows, QA review loops, batch record support, QA on-the-floor interactions, planning and administrative workflows—as well as Engineering and Maintenance activities, including work orders, preventive and corrective maintenance, planning and scheduling, reliability routines, spare parts, calibration, utilities and technical services. You will also oversee Warehouse and Material Flow processes, including receiving, put-away, picking, staging, kitting, line replenishment, inventory counting, material transport, returns, waste flows and warehouse administration.

You will own the lifecycle of standard work, KPI definitions, performance standards, maturity models, diagnostics, cost optimization logic, benchmarking, deployment playbooks and continuous improvement across the network. Your objective will be to establish a repeatable Operating System model that sites can adopt, sustain and continuously improve, rather than delivering isolated improvement projects.

Success will be measured through consistent standard-work adoption, stronger KPI performance, reduced indirect labor intensity, improved quality-process flow, higher maintenance productivity, increased asset availability, better warehouse productivity and measurable cost reduction.

This position is anticipated for a duration of 2 years.

How you will contribute:

Reporting to the Transformation Office Head, you will be responsible to:

• Define the Operating System elements for each modality, including standard work, KPI architecture, performance standards, maturity models, diagnostics, hypothesis trees, process-confirmation checklists and A3 problem-solving logic.
• Translate internal best practices, external benchmarks and site learning into simple, scalable and measurable standards that are practical, auditable, teachable and connected to cost, service, quality, compliance, productivity and capacity outcomes.
• Establish standard work for roles, handoffs, work content, decision points, required data, visual controls and escalation routines.
• Codify the best-known way of working for deviations, CAPA, change controls, investigations, maintenance execution, warehouse activities and other recurring processes.
• Use AVIX or equivalent tools to analyze work content, compare current and target work design, identify non-value-added effort and establish standard time or effort expectations where appropriate.
• Link standard work to process confirmation and leader standard work to sustain adoption.
• Define global KPI hierarchies from enterprise outcomes through site, area and process-level indicators.
• Clarify KPI calculation logic, data sources, review frequency, ownership, target-setting methods and escalation thresholds.
• Set benchmarks for cycle time, productivity, backlog, schedule adherence, flow efficiency, right-first-time, service level, asset availability, inventory accuracy and cost.
• Embed KPIs into LPMS or equivalent daily, weekly and monthly performance routines.
• Identify and quantify opportunities related to indirect labor productivity, process simplification, Quality workflow efficiency, maintenance productivity, warehouse performance, inventory reduction, contractor efficiency and automation.
• Use AVIX, LPMS data and AI-enabled analytics to identify cost drivers, bottlenecks, repetitive losses, performance gaps and improvement opportunities.
• Build value cases linking standard work and KPI improvement to cost, capacity, quality, service and reliability outcomes.
• Track benefit realization and ensure improvements are sustained through management routines and performance standards.
• Identify practical AI, digital and analytics applications for workflow triage, deviation and CAPA pattern detection, maintenance prediction, workload balancing, anomaly detection, KPI narrative generation and opportunity identification.

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