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Hyper-automation and beyond: 3 practical ways AI will transform supply chains in the next 5 years
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The Fourth Industrial Revolution is reshaping supply chain management, replacing traditional methods with digital integration, keeping artificial intelligence (AI) at its core.
India is at the forefront of a digital revolution, experiencing a remarkable evolution driven by AI, restructuring the business landscape. It is evident that the latest innovations will drive significant changes in how organizations operate and make decisions.
According to NASSCOM and BCG, India’s AI market is projected to touch $17 billion by 2027, growing at a rate of 25-35% between 2024 and 2027.
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At the World Economic Forum 2024 in Davos, discussions about AI and its diverse applications were filled with excitement. Amidst the buzz, executives struggled to distinguish practical realities from the hype, highlighting the complexities of harnessing AI's potential for organizational advancement.
Based on my own experiences, as well as what I learned from the 2024 WEF event, here are three predictions about how AI will impact business transformations over the next five years:
Acceleration of domain-specific “Digital Knowledge Models”
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The world’s leading companies continue to grapple with tribal and extremely siloed enterprise knowledge. As a business unit owner, answering to critical questions such as, “Why did sales of ‘Product A’ drop in ‘Market B’ in the last quarter?” or “How can we grow the demand for ‘Product A’ by 10% next quarter, while managing our supply chains effectively?” are often challenging for planners to immediately answer. It takes a collective effort from different experts to share their domain knowledge, and even then, there is no guarantee of timely and detailed answers.
As an industry player, one of the essential lessons for Boards and Chief Experience Officers (CXOs), is to speed up the digitisation of key functional and process areas by transforming their organisation’s tribal knowledge into digital knowledge. I anticipate that within just three years businesses will be judged by the quality of the Digital Knowledge Models that power their operations.
Sustainability supply chain driving ESG opportunities
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Disruptions like the Covid-19 pandemic have shown the need for multi-tier supply chain visibility.
Companies must realise that multi-tier supply chain data will never be perfect. Yet, companies can significantly improve their understanding of critical components and materials risks by building a more comprehensive knowledge model of their supply chain ecosystems to boost efficiency by 10%, 20%, or even 30%, as seen during the pandemic.
Many businesses formed task forces to understand their multi-tier supply chains and vital components, gaining benefits even with manual methods. Moving forward, enterprises must adopt a practical digital model that integrates diverse data sources and fills information gaps through triangulation and predictive modeling.
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Supply chains involve multiple layers, including suppliers, manufacturers, distributors, and retailers. To achieve sustainability goals, enterprises need visibility across all tiers, which is challenging and similar to issues faced during post-pandemic disruptions.
However, ESG objectives may be the catalyst for driving better collaboration with a company’s extended supplier ecosystem. Multi-tier visibility encourages information sharing, helping companies understand Scope 3 emissions from suppliers' activities, crucial for meeting sustainability targets.
To strengthen supply chain resilience, Chief Supply Chain Officers should leverage digital platforms for collaboration and information sharing with suppliers. This includes demand-supply signals, bill of materials, production capacities, and lead times. Open communication on these platforms helps identify issues, meet ESG commitments, reduce environmental impact, and promote sustainable growth.
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Unlock value with hyper-automation and dynamic scenario planning
Many companies struggle with physical forecasting and planning due to changing demand scenarios. Hyper-automation addresses this by eliminating manual forecasting, which often leads to fragmented operations. By digitising tribal knowledge, hyper-automation boosts productivity and planning across domains. It enables touchless processes for comparing planned and actual results, demand forecasting, and operational planning.
Dynamic simulation and scenario planning streamline procurement, production, distribution, and customer response, while breaking down barriers between commercial, finance, and supply chain sectors.
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To stay ahead in India's competitive landscape, companies must prioritise AI-powered integrated planning. This approach seamlessly integrates business functions, enabling accurate forecasting, efficient resource allocation, and rapid market adaptation. By embracing these changes, enterprises can position themselves for innovation and operational excellence, setting them apart as digital transformation trailblazers.
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Chakri Gottemukkala
Chakri Gottemukkala is Co-Founder and CEO of o9 Solutions.