Process Improvement Manager

Siemens AG; Santiago de Querétaro; On-site; MXN 600,000 - 1,200,000; Full time

Job summary

Siemens AG is seeking an Experienced Professional for SCM-Procurement / Supply Chain Logistics in a full-time, office/site role. The position focuses on transforming Planning, Master Data and Order Management processes using AI, automation and data analytics to improve efficiency and data quality.

You will lead end-to-end improvement initiatives, translate business challenges into data-driven solutions, and drive adoption of digital tools across cross-functional teams for measurable impact.

Responsibilities

• Lead end-to-end process improvement initiatives across Planning, Master Data and Order Management to reduce inefficiencies and automate manual activities.
• Define future-state processes focused on simplicity, scalability, automation and data transparency.
• Develop dashboards and models to enable data-driven decision-making and measurable benefits.
• Coordinate with Operations, IT, Engineering and Supply Chain to implement digital tools and AI-enabled solutions.
• Track benefits and sustain improvements with clear baselines, targets and implementation plans.

Job description

SCM-Procurement / Supply Chain Logistics

Company

Experienced Professional

Job type

Full-time

Office/Site only

Employment type

Permanent

Location(s)

Position Purpose

Lead the transformation and continuous improvement of processes within Planning, Master Data and Order Management, leveraging process excellence methodologies, automation, advanced data analytics and Artificial Intelligence to increase efficiency, transparency, data quality and decision-making capabilities.

The role will identify improvement opportunities across the end-to-end operational processes, translate business challenges into data-driven solutions, and lead the implementation and adoption of new digital tools and ways of working.

The position will act as a bridge between business processes, data and technology, ensuring that digitalization and AI initiatives generate measurable operational impact rather than remaining isolated technology projects.

Key Responsibilities

1. Process Improvement & Operational Excellence

• Analyze existing Planning, Master Data and Order Management processes to identify inefficiencies, bottlenecks, manual activities and opportunities for standardization.
• Lead end-to-end process improvement initiatives with the relevant stakeholders.
• Define future-state processes focused on simplicity, scalability, automation and data transparency.
• Establish process standards, governance and performance indicators.
• Facilitate structured problem-solving and root-cause analysis.
• Build a continuous improvement culture within the organization.
• Identify opportunities where large volumes of operational data can be converted into actionable business insights.
• Develop and promote data-driven decision-making across Planning, Master Data and Order Management.
• Define business requirements for dashboards, analytical models and decision-support tools.
• Connect information from different processes and systems to improve end-to-end visibility.
• Develop use cases for predictive and advanced analytics.
• Work with technical experts to convert operational requirements into scalable data solutions.

3. Artificial Intelligence & Automation

• Identify and prioritize opportunities to apply AI, Generative AI, Machine Learning and process automation to operational processes.
• Develop use cases focused on reducing repetitive work, improving decisions and accelerating information analysis.
• Lead proof-of-concept initiatives and support their transition into sustainable business solutions.
• Promote responsible adoption of AI tools within the organization.
• Support teams in integrating AI into their daily workflows and decision-making processes.

Potential applications could include:

• demand and workload analysis
• order prioritization
• exception management
• automatic identification of data inconsistencies
• root-cause analysis
• forecasting support
• automated generation and interpretation of operational KPIs
• Create and manage a Process Improvement & Digitalization Roadmap for the department.
• Maintain a structured pipeline of improvement opportunities and digital use cases.
• Evaluate initiatives based on business impact, effort, complexity and scalability.
• Define priorities together with department leadership.
• Coordinate initiatives involving Operations, IT, Engineering, Supply Chain and other relevant functions.
• Track benefits and ensure improvements are sustained after implementation.

5. KPI & Performance Management

Establish measurable impact for improvement initiatives, such as:

• process lead-time reduction
• productivity improvement
• reduction of manual activities
• data-quality improvement
• planning accuracy
• order-processing performance
• reduction of operational exceptions
• user adoption of digital solutions
• reduction of repetitive reporting activities

The role should ensure that every improvement initiative has a baseline, target, implementation plan and measurable business benefit.

6. Change Management & Capability Building

• Promote a digital and continuous-improvement mindset within the organization.
• Train and coach employees in process improvement, data analytics and AI-supported ways of working.
• Facilitate workshops to identify improvement opportunities and digital use cases.
• Support implementation and adoption of new processes and tools.
• Build a network of process-improvement and digitalization champions within the organization.

Experience

Education

Siemens is committed to equal opportunities and non-discrimination. We value diversity and foster inclusion in our workplace. All employment decisions are based on qualifications, merit, and business needs, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other characteristic protected by law.