Over the past two decades, technology has revolutionised various sectors. Companies like Uber and Ola have transformed transportation, while Zomato and Swiggy have reshaped consumer dining habits. Similarly, Tesla has redefined the automotive industry’s approach to electric vehicles, among numerous other examples across different fields.
The manufacturing sector stands out as a prime illustration of technology’s transformative power, significantly impacting national economies. According to a study by the McKinsey Global Institute, industry front runners adopting Artificial Intelligence (AI) now could see a cumulative increase in cash flow of 122 percent over the next five to seven years, compared to a mere 10 percent for those who lag behind. This represents a substantial opportunity. Manufacturing firms have, and will continue to, benefit greatly from technologies like AI, the Internet of Things (IoT), 5G, cloud computing, and edge computing, provided these are implemented effectively.
Understanding the contribution of each technology is crucial for leveraging their potential.
The Role of AI, IoT, Cloud, and Edge Computing in Manufacturing Transformation
The advent of Industry 4.0 has propelled India into a leading position globally, contributing to its status as one of the fastest-growing economies. As a matured, technology-first nation, the technological enablement of manufacturing has played a significant role.
Industry 4.0 marks a transition from centralised to decentralised manufacturing, necessitating an integrated approach that includes AI, IoT, cloud and edge computing, analytics, and more.
Increased Efficiency: The manufacturing sector now generates vast amounts of data through extensive sensor use and advanced technologies. Manufacturers can make data-driven decisions to minimise machine downtime and optimise capabilities for maximum returns. Real-time monitoring and adjustments streamline operations, enhancing planning and operational efficiency, which significantly impacts both revenue and profit margins.
Cost Reduction: Analysing historical data enables manufacturing companies to forecast production demand and improve inventory management through tracking systems, increasing operational visibility and optimising costs. Efficient operations also enhance customer satisfaction by producing high-quality products at lower costs.
Improvement in Product Quality: Technological advancements help improve product quality. For example, robots increase efficiency and reduce human risk by performing tasks faster. Automation and optimisation of the supply chain also contribute to higher product quality.
Real-world Examples:
- GlobalFoundries has invested heavily in automation and robotics in their New York facility to minimise errors and improve production times.
- Accenture uses Celonis’ AI-based process mining to refine operations at Mann+Hummel, a German manufacturer specialising in filtration technology.
These examples underscore the tangible benefits of technological transformation, which, however, is not without challenges.
One major obstacle is skilling the workforce to manage these new technologies effectively. Future-proofing is also essential, requiring a clear vision and roadmap that drives transformation, rather than being led by it. A business-first approach, facilitated by technological advancements, is crucial for sustaining competitive advantages and requires a long-term vision that goes beyond immediate fixes.
Organisations face other challenges, such as scaling beyond initial successes and managing diversity in IT environments and machinery, which demand immediate attention.
Drawing inspiration from Star Wars, “Digital transformation is not about technology—it’s about change.” Leaders should view digital transformation as a shift in mindset and organisational culture rather than merely a technological upgrade.
