Data Science for Operational Excellence

Classroom

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Online / Live

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Introduction

Course overview

Why Attend
Operational excellence depends on efficient processes, reliable decisions, continuous improvement, and the ability to respond quickly to change. Data science enables organizations to uncover inefficiencies, predict outcomes, optimize resources, and improve performance using evidence rather than assumptions. This course provides participants with practical tools to apply data science concepts, analytics techniques, and digital technologies to achieve stronger operational results.

Course Methodology
This course uses an interactive and practical approach through presentations, case studies, analytics workshops, group discussions, dashboards exercises, process improvement activities, and real business examples.

Course Objectives

Understand the relationship between data science and operational excellence
Use data for smarter operational decision-making
Improve data quality, governance, and reporting practices
Apply analytics to optimize processes and workflows
Use forecasting for planning capacity and resources
Integrate Lean improvement with data-driven methods
Build a sustainable culture of continuous improvement
Align analytics initiatives with business strategy

Target Audience

Operations Managers
Process Improvement Professionals
Business Analysts
Supply Chain Managers
Quality Managers
Project Managers
Anyone responsible for performance improvement and operations

Target Competencies

Data Analysis
Operational Excellence
Process Optimisation
Forecasting
KPI Management
Continuous Improvement
Strategic Thinking
Decision-Making

What you will achieve

Learning objectives

Understand the relationship between data science and operational excellence
Use data for smarter operational decision-making
Improve data quality, governance, and reporting practices
Apply analytics to optimize processes and workflows
Use forecasting for planning capacity and resources
Integrate Lean improvement with data-driven methods
Build a sustainable culture of continuous improvement
Align analytics initiatives with business strategy

Who should attend

Target audience

Operations Managers
Process Improvement Professionals
Business Analysts
Supply Chain Managers
Quality Managers
Project Managers
Anyone responsible for performance improvement and operations
Target Competencies

Methodology

Learning approach

This course uses an interactive and practical approach through presentations, case studies, analytics workshops, group discussions, dashboards exercises, process improvement activities, and real business examples.

Course content

Five focused days of learning and application

Day 1

Foundations of Data Science and Operational Excellence

Growth of data in modern organizations
Principles of operational excellence
Why data-driven decisions outperform intuition alone
Sources of operational data: internal and external
Descriptive, predictive, and prescriptive analytics overview
Successes and failures of analytics in operations
Key tools and technologies used in data science
Building a data-driven culture foundation

Day 2

Tools, Techniques, and Data Management

Data collection, storage, and governance essentials
Improving data accuracy, consistency, and timeliness
Data visualization for operational clarity
Introduction to analytics platforms and tools
Dashboards for real-time operational monitoring
Statistical methods for process control and improvement
Managing large datasets and unstructured information
Ethical and responsible use of data

Day 3

Applying Data Science to Process Optimisation

Using data to identify bottlenecks and waste
Combining Lean Six Sigma with analytics
Predictive analytics for demand and resource planning
Machine learning concepts for workflow optimisation
KPIs for operational excellence
Practical exercise: analyse an operations dataset
Supply chain optimisation through analytics
Designing a data-led improvement roadmap

Day 4

Driving Continuous Improvement with Analytics

Embedding analytical thinking across departments
Advanced analytics for risk management and resilience
Automation and AI opportunities in operations
Presenting insights to decision-makers effectively
Overcoming resistance to data adoption
Building sustainable improvement systems
Solving operational problems with data methods
Reflection and workplace application planning

Day 5

Strategic Integration and Future Readiness

Integrating data science into long-term operations strategy
Aligning analytics with goals and performance targets
Advanced forecasting for capacity, risk, and resources
Scaling successful initiatives across business functions
Governance for sustainable data-driven operations
Continuous improvement through analytics maturity
Final case study and action plan
Course review and next steps

FAQ

Frequently asked questions

What does Data Science for Operational Excellence (DMBI-016) cover?

This course covers Data Management and Business Intelligence through a structured five-day outline focused on practical application, discussion, and implementation planning.

When is the next available session?

The next scheduled session starts on Schedule on request, with additional classroom dates and mirrored Online / Live options listed in the course schedules section.

Who should attend this course?

Operations Managers, Process Improvement Professionals, Business Analysts

How can I register for a session?

Use any Register button next to the available course dates to open the participant registration page and submit your booking request for the selected session.

Is this course available online as well as classroom-based?

Yes. The course detail page includes both classroom sessions and Online / Live sessions, with online options aligned to the same course dates for easier planning.

Where are classroom sessions delivered?

Classroom venues are confirmed in the schedule panel for each published session.

Still Have Questions?

Contact the academy team for course details, delivery options, and delegate guidance.

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