GenAI has the potential to redefine how supply chains function and adapt to demands. Interestingly, there are also fascinating synergies between the strategic complexities of cricket and the predictive capabilities of supply chain management (SCM).
The potential of India’s supply chain infrastructure
Thanks to its robust economic growth, India is on track to become a global economic powerhouse. However, its supply chain infrastructure must evolve to keep pace. India’s complex web of supply chain processes, including procurement, manufacturing, distribution and logistics, creates multiple points of vulnerability.
The global AI in supply chain and logistics market is projected to grow at a CAGR of 19.43%, reaching 15 billion US dollars By 2028, the role of AI, with the help of data analysis and the integration of computer vision, will become increasingly important.
Cricket and supply chain management: parallels in strategic decision making
In cricket, players must make split-second strategic decisions that can determine the outcome of the game. This uncanny ability to predict and respond parallels the evolution of supply chain planning. GenAI enables businesses to anticipate market dynamics and orchestrate proactive strategies, shaping a path to operational excellence and success.
The essence of predictive analytics and holistic planning lies at the heart of the strategic game of cricket and the transformative influence of GenAI on SCM.
The Three Ws of Cricket and SCM Powered by GenAI
Just as cricketers assess the pitch, anticipate the trajectory of the ball and determine the most effective shot, supply chain management revolves around three fundamental questions:
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- What happened and why?
- What is likely to happen?
- What actions should be taken?
Cricketers analyse past plays, conditions and opponents’ strategies to anticipate the next move. Similarly, in GenAI-powered SCM, companies analyse data, current market trends, customer demand and potential disruptions to predict future scenarios.
The “three Ws of planning” – understanding past events, anticipating future outcomes and strategizing action – form the cornerstone of both the tactical finesse of cricket and the transformative capabilities of GenAI within SCM.
As cricketers adjust their game based on analytics, companies must devise strategies that mitigate risks, capitalize on opportunities and steer the supply chain toward optimal performance.
Below are some ways GenAI can be applied to improve supply chain planning:
Predictive analytics for proactive supply chain management:
GenAI enables supply chain management professionals to move from reactive to proactive management by providing them with predictive insights derived from robust data analysis. This enables anticipation and preparation for future scenarios and events. It tailors solutions to specific supply chain management challenges, customizing each unique context by leveraging data to provide accurate decision support and fine-tune complex models without compromising resources.
Prototyping based on large language models to succeed:
Using GenAI prototypes is the key to efficient supply chain planning. Atomic agents based on large language models (LLM) are systems supported by AI technologies capable of performing simple tasks, retrieving information, and generating responses to queries. These atomic agents, along with LLM systems, efficiently handle critical tasks such as seamlessly generating reports and rapidly modifying data, ultimately improving overall productivity.
Complementing these capabilities, LLM-powered composite elements build on atomic agents by integrating a sequence of basic tasks to perform more complicated activities essential to cross-functional planning processes, such as creating forecasts or performing post-game analysis. Composite elements accomplish this by retrieving and synthesizing data relevant to an outcome. Applicable use cases include analyzing forecast differences from quarter to quarter or delivering a post-game analysis of the prior month to compare the prior forecast to actual results.
Furthermore, composite agents continuously improve by learning from feedback. They can provide comprehensive strategic decision-making insights for cross-functional teams and perform complex functions such as complex scenario simulations. In addition, the adaptable LLM-based model configurator enables companies to customize models and integrate new measures, tailoring solutions precisely to their specific requirements.
How to address value loss in supply chains
Managing value leakage in supply chain operations is a widespread challenge for many large companies. This process often results in inefficiencies and missed opportunities, prompting companies to seek innovative solutions. Key measures to overcome value leakage include:
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- Education and Alignment: Facilitate understanding and acceptance of GenAI among stakeholders.
- Implementation: Support seamless integration of GenAI into existing systems.
- Creating value: Leverage GenAI to optimize planning and improve operational efficiency.
- Continuous improvement: Emphasize iterative learning for continuous supply chain improvement.
Conclusion
The synergy between cricket and GenAI in supply chain management highlights the universal importance of predictive insights. Just as a cricketer’s reading influences the match, AI-powered foresight shapes supply chains, guiding them to excel amidst evolving business landscapes. By embracing these parallels, businesses can harness the full potential of GenAI to drive strategic decision-making and achieve operational success.
—The author, Siddhartha Niyogi is the Managing Director and CEO of o9 India. A leading AI-powered platform for integrated business planning and decision making for enterprises. The views expressed are personal.
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