AI in Supply Chain
When faced with a pandemic like COVID-19, establishing a good understanding of the impact on supply chains and contingency plans can help manufacturing companies deal with uncertainties in the right way.
The COVID-19 epidemic has resulted in severely affecting thousands of supply chains globally, the economic impact of which will linger for months to come.
According to The Organisation for Economic Co-operation and Development (OECD), the Coronavirus could cut global economic growth in half, with several industries across the board facing a major fall off. China, the world’s second-largest economy and several internal supply chains plunged as the Coronavirus spread from here to other countries in Asia, Australia, Europe, the Americas, and the Middle East. As a result, preventive actions that intended to block the further spread of the virus, including travel restrictions and large scale quarantine, have only resulted in further plummeting and disrupting global food, retails and medical supply chains, halting critical business operations and freezing revenues.
A recent survey by the Institute For Supply Chain Management, nearly 75% of companies reported some sort of supply chain disruptions owing to coronavirus-related transportation restrictions, and the figure is expected to rise further over the next few weeks. This, in fact, is just one of the many facets of the global COVID-19 impact but a significant one.
Further, a study from Dun & Bradstreet suggests on a global level, 51,000 companies have “one or more direct or Tier 1 supplier,” from China and an additional five million companies have Tier 2 suppliers there, with 938 of those being Fortune 1000 companies.
The Impact on Supply chains is twofold –
First, companies must closely monitor short-term and long-term demand and inventory to account for any production loss in case of factory closures and economic slowdown.
Second, retailers who are faced with inventory depletion as consumers stock up for potential quarantine or extended stays at home. This has severely affected the smooth supply chain functioning across the globe due to the “panic buying” ripple effect.
Few questions that arise as a result of the above:
- How can food and retail supply chains use the power of Artificial Intelligence (AI)-lead advanced analytics to plan, prepare and manage this crisis?
- How can manufacturers effectively leverage AI to manage demand volatility and mitigate this supply shock?
- How can AI-lead intelligent automation and analytics help create contingency plans and create safe working environments?
Benefits of AI-Powered Supply Chains
Studies suggest that AI and Machine Learning (ML) can deliver unprecedented value to supply chain and logistics operations. From cost savings through reduced operational redundancies and risk mitigation, to enhanced supply chain forecasting and speedy deliveries through more optimized routes to improved customer service, AI-enabled supply chains are being preferred by several manufacturers globally.
According to McKinsey, 61% of manufacturing executives report decreased costs and 53% report increased revenues as a direct result of introducing AI into their supply chains. Further, more than one-third suggested a total revenue bounce of more than 5%. Some of the high impact areas in supply chain management include sales and demand, forecasting, spend analytics, and logistics network optimization.
AI matters the most to supply chain operations today, and here’s why:
1. End-End Visibility:
With the complex network of supply chains that exist today, it is critical for manufacturers to get complete visibility of the entire supply value chain, with minimal effort. Having a cognitive AI-driven automated platform offers a single virtualized data layer to reveal the cause and effect, to eliminate bottleneck operations, and pick opportunities for improvement. All of this using real-time data instead of redundant historical data.
2. Intelligent Decision-Making:
AI-lead automation amplifies important decisions by using cognitive predictions and recommendations on optimal actions. This can help enhance overall supply chain performance. It also helps manufacturers with possible implications across various scenarios in terms of time, cost, and revenue. Also, by constantly learning over time, it continuously improves on these recommendations as relative conditions change.
3. Adequate Supply Chain Planning:
Machine Learning can help by providing the best possible demand scenarios based on intelligent algorithms and machine-to-machine analysis of big data sets. This is possible by using work tools that run in a continuous loop. This kind of intelligent capability could optimize the delivery of goods while balancing supply and demand. This also wouldn’t need any human intervention based analysis for the setting of parameters.
4. Actionable Analytical Insights:
Several companies today, lack key actionable insights to drive timely decisions that meet expectations with speed and agility. Cognitive automation that uses the power of AI has the ability to sift through large amounts of scattered information to detect patterns and quantify tradeoffs at a scale, much better than what’s possible with conventional systems.
5. Improved Warehouse Management:
The warehouse is the powerhouse for supply chain activities and if there is a glitch here, manufacturers can miss valuable revenue generation opportunities. AI-lead automation of warehouse procedures leverages smart supply chain management technologies to simplify processes, speed up operations, and reduce the dependence on manual tasks throughout the supply value chain.
Supply Chain Optimization and AI
According to PwC, AI applications have the power to transform the way business is done and contribute up to $15.7 trillion to the global economy by 2030. Today, AI can seed in the much needed exceptional agility and precision in supply chain optimization. It can also trigger a transformational increase in operational and supply chain efficiencies and a decrease in costs where repetitive manual tasks can be automated.
Click here to know how choosing a good Supply Chain Optimization Software can help manufacturers leverage AI-enabled efficiencies for optimum results.