With complex supply chains expanding globally and increasing competition in the digital space, a small error can be catastrophic and lead to loss of productivity. As a result, there is an increased demand for superlative efficiency between the nodes in a supply chain to maximise throughput and reduce uncertainties. Add to that the aggravated market volatility and the need for artificial intelligence in supply chains become apparent.
AI in supply chain and logistics
Artificial intelligence and machine learning are already at work, changing the way sourcing subcontractors operate. By integrating multiple functions like marketing, sales, procurement, logistics, etc., digital and AI enable industry-wide visibility into the supply chain.
With proper integration, companies can address the current supply chain shortcomings and prepare for the future ones in this “new normal”. There are already several channels of data collection, which quality control experts can leverage to process operations, perform predictive maintenance, and optimise the supply chain for maximum efficiency.
What the AI-led transformation of the supply chain entails for businesses
Strategies for value creation
Firms will need to identify the value creation opportunities in the current market and prioritise the functions based on the expected ROI. Independent diagnostics across functions like manufacturing, procurement, and logistics will help support the business strategy and create a roadmap to align all functions for maximum value creation.
Designing the target solution and vendor selection
The market disruption brought on by the COVID pandemic led to companies understanding the importance of working with several suppliers. Organisations need to comprehend the importance of end-to-end solutions and how they can support the existing functions. With the implementation of AI, companies can predict the best approach and adjust their processes based on the data from quality control experts.
Systems integration
AI will also help companies gain the required experience to implement upgrades on an industry-wide basis. Over the last decade, cloud-based applications for enterprise resource management, manufacturing systems, and warehouse planning systems have been integrated with AI and analytics, which takes away the menial tasks and creates space for strategising about value creation. With a proper roadmap, organisations can execute system integrations within a budget while delivering short- and long-term value.
Inventory management and warehouse efficiency
Streamlined inventory management allows organisations to avoid running into delivery delays or unnecessary logistics costs. AI has already improved warehouse efficiency by a centralised inventory repository, which prevents excess inventory in one area and not enough in another. In addition, when the sourcing subcontractors are agile, they can respond to increased demand in time and ensure that the deliveries don’t miss deadlines.
AI is the much-needed help required to handle complex supply chains with ease. Organisational changes with AI integration will not only help update the business processes, but it will also upskill the efforts, and the difference between winners and losers will become apparent.
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