MODULE – 1 : Introduction to Digital Transformation
About the Module:
This module provides a foundational understanding of Digital Transformation, a critical process that modern businesses must undergo to stay competitive in today’s technology-driven world. It explores how Digital technologies, including Automation, Cloud computing, Data analytics, Artificial intelligence (AI) including Generative AI, and the Internet of Things (IoT), are reshaping industries and changing the way businesses operate.
Participants will examine the various stages of Digital Transformation, from the adoption of basic Digital tools to the implementation of comprehensive Digital strategies. The module also covers the key drivers of Transformation, the potential challenges companies face, and the opportunities that come with embracing Digital innovation.
By the end of this module, participants will understand why Digital Transformation is more than just a Technological upgrade – it’s a holistic business strategy that requires changes in culture, leadership, and processes to succeed.
Concepts Covered :
- Understanding Digitization, Digitalization & Digital Transformation
- Introduction to Digital Masters & characteristics
- Evolution of Digital Transformation
- Key Drivers of Digital Transformation
- Industry specific Digital Disruption
- Role of Data & Analytics in Digital Transformation
- Disruptive Innovation – Clayton Christensen’s Theory
- Stages of successful Digital Transformation
- Case Studies – Successes & Failures of Transformation in Industry
Learning Outcomes:
Understand the Concept of Digital Transformation:
Define Digital Transformation and recognize its significance in modern industries.
Digital Masters & their characteristics
Differentiate between Digitization, Digitalization, and Digital Transformation.
Identify the Key Drivers of Digital Transformation:
Explain the major factors driving the need for Digital Transformation, such as customer expectations, technological advancements, and market competition.
Discuss how emerging technologies (e.g., AI, IoT, Cloud Computing) are enabling businesses to innovate and stay competitive.
Explore Examples of Digital Transformation in Various Industries:
Analyze case studies of companies that have successfully implemented Digital Transformation across sectors such as manufacturing, retail, healthcare, and finance.
Evaluate the impact of Digital Transformation on business models, customer experiences, and operational efficiency.
Learn the Phases and Stages of Digital Transformation:
Explore the various stages of Digital Transformation, from initiating small Digital projects to scaling and integrating Digital tools across the entire organization.
Understand how companies can progress from being Digital beginners to becoming Digital masters.
MODULE – 2 : Digital Business Concepts & Leading Digital Technologies
About the Module:
This module explores the concept and evolution of Digital Business, contrasting traditional and Digital business models, and highlighting the types of Digital businesses that exist today. A focus is placed on building organizational resilience within the Manufacturing industry through Digital initiatives and the need for innovation-led Digital Transformation, supported by relevant case studies.
Key drivers for business Transformation in Manufacturing are discussed, emphasizing the role of Technology in achieving competitive differentiation.
Participants will learn about the five domains of a Digital strategy and explore leading Digital Technologies, including machine learning (ML), generative AI, RPA, immersive technologies like AR & VR, IoT, blockchain, and 3D printing, along with practical industry use cases.
Finally, it addresses how to execute a balanced integration of emerging technologies aligned with organizational goals.
Concepts Covered:
• The Power of Technology led Disruption
• Definition & evolution of Digital Business
• Types of Digital Business
• Difference between Traditional and Digital Business Models
• The 5 domains in a Digital Strategy
• Competencies for measuring Digital Business Maturity
• Walkthrough of approx. 30 Leading Digital technologies viz ML, Generative AI, RPA, Immersive technologies like AR & VR, IoT Technology, Blockchain, 3D Printing in Automotive etc.
• Use cases / Examples of deployment of these technologies in Industries
• Importance of executing the right mix of emerging technologies aligned with organizational goals
Learning Outcomes:
• Understand Digital Business: Grasp the definition, evolution, and types of Digital business, and how they differ from traditional business models.
• Build Organizational Resilience: Learn how to leverage Digital technologies to build organizational resilience, particularly in the Manufacturing Industry.
• Understand Digital Business Maturity frameworks for measuring Digital Maturity
• Formulate Digital Strategy: Explore the five key domains of a Digital strategy and how they can be applied to drive successful Digital innovation within an organization.
• Familiarize with Key Digital Technologies: Gain an understanding of major Digital technologies such as ML, Generative AI, RPA, AR & VR, IoT, Blockchain, and 3D Printing
• Analyze Real-World Use Cases: Learn from industry examples and use cases showcasing the successful deployment of these technologies.
MODULE 3 & 4: Driving Digital Transformation in Industry – Part 1 & 2
About the Module:
This module on ‘Driving Digital Transformation in Industry’ is 2 in Parts and provides an in-depth exploration of how organizations leverage cutting-edge Digital technologies to drive innovation, streamline operations, and enhance customer experiences. The module begins by focusing on the fundamentals of Digital business Transformation, examining how organizations use technologies like automation, data analytics, and connected products to remain competitive in today’s fast-paced Digital landscape. Students will explore the growing importance of Digital Product Management and the Platform economy, understanding how Organizations have revolutionized industries by building ecosystems that enable seamless user experiences and scalability.
The module also delves into the principles of Design thinking and Empathy-led innovation, equipping students with the skills to craft customer-centered solutions by means of a Virtual Design Thinking Workshop using a Case study. Special emphasis is placed on Open and Disruptive innovation, where students will learn how external collaborations and breakthrough technologies are reshaping business models across sectors. The Module also covers Agile methodologies, giving students a solid foundation in iterative processes that allow businesses to rapidly adapt to changes and deliver value faster. These concepts are further contextualized within the framework of the seven pillars of Digital Transformation, including customer experience, process automation, Industry 4.0, and cybersecurity.
Finally, the module offers a Deep dive into Industry 4.0, focusing on the integration of IoT, AI, and advanced robotics to create smart, automated production environments. Additionally, students will learn the critical role of Change Management in ensuring successful Digital Transformation, particularly how businesses can align their processes, people, and strategies to adopt Technological shifts seamlessly. The course concludes with insights into Value management and Business Process Re-engineering (BPR), providing a comprehensive toolkit for leading Transformation in various industries.
Concepts Covered:
- Business Transformation leveraging Digital Technologies
- Digital Product Management & Platform Economy
- Introduction to Digital Innovation
- Design Thinking & Empathy led Innovation
- Open & Disruptive Innovation
- Overview of Agile Methodologies
- The Pillars of Digital Transformation in Industry
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- Customer Experience (CX) Transformation
- Process Automation
- Data & Analytics
- Connected Products
- Industry 4.0
- Employee Engagement
- Cybersecurity
- Value Management & Business Process Re-engineering (BPR)
- Deep Dive – Industry 4.0
- Role of Change Management in Digital Transformation
Learning Outcomes:
- Understand the concept of Digital Product Management & Platform economy.
- Apply Design thinking and Empathy-led innovation techniques to develop user-centric solutions.
- Understand Open innovation frameworks and how to leverage Disruptive technologies.
- Implement Agile methodologies to enhance project delivery and responsiveness.
- Evaluate the seven pillars of Digital Transformation and their application in real-world scenarios.
- Develop strategies for value management and effectively re-engineer business processes.
- Gain specialized knowledge in Industry 4.0 technologies and their impact on Manufacturing and Production.
- Manage change effectively by applying best practices in change management during Digital Transformation initiatives.
MODULE 5 : Digital Transformation in Automotive / eMobility Industry
About the Module:
This module on Digital Transformation in Automotive and E-Mobility delves into the integration of cutting-edge Digital technologies reshaping the automotive industry. It explores how the industry is transforming through the adoption of connected, autonomous, shared, and electric (CASE) vehicles, emphasizing the role of Digital Platforms and data-driven innovation. Students will gain insights into how automakers and mobility providers are using advanced Digital technologies like AI, IoT, and 5G to create smarter, more efficient, and customer-centric transportation solutions.
The Module will also focus on E-Mobility, detailing the infrastructure and Digital ecosystems required to support electric vehicles (EVs). It covers topics like EV charging networks, battery management systems, and Digital Platforms that integrate with Transportation and energy grids. Additionally, the module emphasizes the importance of sustainable mobility solutions, leveraging data and analytics to optimize electric vehicle performance and environmental impact.
Finally, the module highlights the pivotal role of Industry 4.0 technologies in transforming automotive manufacturing, including smart factories, robotics, and additive manufacturing. Students will explore how companies are implementing these technologies to enhance productivity, reduce costs, and improve supply chain resilience, while also adapting to the evolving regulatory environment around vehicle safety, data privacy, and cybersecurity.
Concepts Covered:
- Challenges for Urban Mobility in 2030
- Urban Mobility 2030 : – Technology Capability Areas
- Deep dive into various Technologies & Trends impacting Mobility in 2030
- 5C’s – Customer, Company, Channel, Collaborator and Community
- Different Business model – Direct sales, Mobility as a Service, Energy as a Service, Charging Management and Battery Swapping
- Pillars and foundation – Smart Product, Sales, Industry 4.0, Cloud security
- Digital for sales – complete mapping from presale to Rebuy / Scrap
- Driver engagement module
- Digital Automotive Security
- Connected Vehicles Global Landscape
- Uptime solution centre and Flashing Over the Air.
- Charging as a Service – locate charger, Book a slot, Digital Payment, Revenue booking & sharing
- Battery swapping – discussion on Tech Intervention like swap station locator, availability of battery, Book the battery, Payment on the go & Infinite Range
- How new Business Models are being powered by Digital Twins?
- Examples of various types of Digital Twins
- Definition of Digital Twin & Characteristics of a Digital Twin
- How Digital Twin enables differentiation in Automotive?
- Sensorization Strategy in Automotive for building a Digital Twin
- Technologies enabling Digital Twin
- How to build a Digital Twin of a vehicle?
Learning Outcomes:
Understand the Role of Digital Technologies in Automotive:
Students will be able to explain how Digital technologies like AI, IoT, and 5G are transforming the automotive industry and enabling connected, autonomous, and electric vehicles (CASE).
Analyze the E-Mobility Ecosystem:
Students will explore and critically assess the infrastructure, including EV charging networks and battery management systems, that support the growth and adoption of electric vehicles.
Evaluate Industry 4.0 in Automotive Manufacturing:
Learners will evaluate the impact of Industry 4.0 technologies such as smart factories, robotics, and additive manufacturing on automotive production, focusing on efficiency and sustainability.
Understand Data-Driven Innovation:
Students will gain the ability to leverage data and analytics to optimize vehicle performance, improve customer experiences, and make mobility services more efficient and sustainable.
Examine Sustainable Mobility Solutions:
Learners will explore how Digital Transformation supports the transition to sustainable mobility, focusing on reducing the environmental impact of automotive operations and e-mobility services.
Address Regulatory and Cybersecurity Challenges:
Students will be able to identify and discuss key regulatory, cybersecurity, and data privacy challenges in the automotive and e-mobility space, as Digital systems become more integral to vehicle operations and customer interactions.
These outcomes are designed to ensure students develop a comprehensive understanding of both the technological advancements and the broader implications of Digital Transformation in the automotive and e-mobility sectors.
MODULE 6 : AI Concepts & application of AI in Industry including Generative AI
About the Module:
This module offers an in-depth understanding of AI concepts and their applications in various industries, including the rapidly evolving Generative AI. Starting with the fundamentals, students will explore key AI concepts such as Supervised Learning, Unsupervised Learning, and Deep Learning, along with foundational elements required to implement AI in organizations.
The Module covers the strategic alignment of AI initiatives with business goals, focusing on how AI technologies can drive business value in industries like automotive, manufacturing, and supply chain management.
Students will explore real-world use cases of AI, such as Predictive maintenance, Vehicle health monitoring, and enhancing Customer experiences through personalization and data-driven insights. The module also addresses ethical challenges and the future trajectory of AI, emphasizing the importance of building an AI-ready culture.
Key topics include scaling AI solutions, model deployment, and strategies to overcome common barriers to AI implementation, such as data governance and change management.
Concepts Covered:
AI Concepts: Supervised learning, Unsupervised learning, Deep learning etc.
Foundations of AI Implementation: Understand the key principles and prerequisites for successfully deploying AI across an organization, including data readiness and infrastructure requirements.
AI Strategy Alignment: Learn how to align AI initiatives with overall business strategy, ensuring that AI projects drive value and support organizational goals.
AI Use Cases in Industry: Discuss AI’s use in predicting vehicle failures, optimizing vehicle health monitoring, and improving efficiency in automotive manufacturing and supply chain management.
AI for Personalization and Customer Experience: Examine how AI enhances in-car user experiences, personalizes settings, and uses data-driven insights to improve customer engagement.
Ethical Considerations and Future Trends: Address ethical challenges, regulatory frameworks, and future trends in AI that could shape the automotive industry and smart mobility innovations.
Building an AI-Ready Culture: Explore the importance of fostering a culture that embraces AI, including upskilling employees, encouraging experimentation, and promoting collaboration between AI teams and business units.
Operationalizing AI at Scale: Delve into practical approaches for scaling AI solutions across the enterprise, covering model deployment, monitoring, and continuous improvement to ensure sustained success.
Overcoming Common Scaling Challenges: Identify and address common obstacles to scaling AI, such as data governance, ethical considerations, and change management, with strategies for overcoming these challenges.
Learning Outcomes:
Understand Core AI Concepts:
Define and distinguish between Supervised Learning, Unsupervised Learning, Deep Learning, and other AI methodologies.
Apply AI Use Cases in Industry:
Evaluate the application of AI in industries such as automotive, particularly in predicting vehicle failures, optimizing manufacturing processes, and improving supply chain efficiency.
Recognize AI Implementation Requirements:
Identify the key principles and prerequisites for successfully deploying AI solutions, including data readiness and infrastructure needs within an organization.
Align AI with Business Strategy:
Analyze how to align AI initiatives with broader business strategies, ensuring that AI contributes to achieving organizational goals and provides tangible business value.
Leverage AI for Personalization:
Explain how AI enhances personalization and customer experience, especially in in-car systems and consumer-facing technologies.
Address Ethical and Regulatory Challenges:
Discuss the ethical considerations, regulatory frameworks, and future trends impacting AI adoption, particularly in smart mobility and industry sectors.
Build an AI-Ready Culture:
Understand the importance of fostering an AI-ready culture, emphasizing the need for employee upskilling, cross-team collaboration, and experimentation to promote AI-driven innovation.
Operationalise AI at Scale:
Learn the practical aspects of scaling AI solutions across the enterprise, focusing on model deployment, monitoring, and continuous improvement to ensure sustained success.
Overcome AI Scaling Challenges:
Identify common challenges in scaling AI, such as data governance, ethical issues, and change management, and propose strategies to overcome these obstacles.
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