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How can AI improve supply chain efficiency?

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Supply chain efficiency is crucial for any business that wants to deliver products or services to customers on time, on budget, and with high quality. However, managing a complex and dynamic supply chain can be challenging, especially in the face of uncertainties, disruptions, and changing customer demands. That's where artificial intelligence (AI) can help. AI is the ability of machines to perform tasks that normally require human intelligence, such as learning, reasoning, and decision making. In this article, you will learn how AI can improve supply chain efficiency in four key areas: demand forecasting, inventory optimization, logistics planning, and quality control.

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Sushmita Nath

OTM-GTM Cloud Certified Consultant| | WMS | Supply Chain Management | BI| Logistics |Analytics| ML| Python| Data…

1 Demand forecasting

Demand forecasting is the process of estimating the future demand for a product or service based on historical data, market trends, and customer behavior. Accurate demand forecasting can help businesses plan production, allocate resources, and reduce waste. However, traditional methods of demand forecasting, such as statistical models or expert opinions, can be inaccurate, biased, or outdated. AI can improve demand forecasting by using machine learning algorithms to analyze large and diverse data sets, such as sales records, weather patterns, social media sentiment, and competitor actions. AI can also adapt to changing conditions and provide real-time updates and recommendations.

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Sushmita Nath

OTM-GTM Cloud Certified Consultant| | WMS | Supply Chain Management | BI| Logistics |Analytics| ML| Python| Data Analysis with Python| Data Science, AI Enthusiast
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Demand forecasting is one of the important process in case of eCommerce or even food industry and small biz as well.There are startups who are already working on it I believe or have the solution for it.In general Demand forecasting plays much important role in Warehouse management,where they need to forecast item, quantity requirement...also so that it's not wasted or specifically food items which has expiry date needs higher level of forecasting.

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2 Inventory optimization

Inventory optimization is the process of balancing the supply and demand of goods or materials in a supply chain. Too much inventory can lead to high storage costs, spoilage, and obsolescence. Too little inventory can lead to stockouts, lost sales, and customer dissatisfaction. Inventory optimization aims to find the optimal level of inventory that minimizes costs and maximizes service levels. AI can improve inventory optimization by using deep learning techniques to model complex and nonlinear relationships between inventory variables, such as demand, supply, lead time, and replenishment frequency. AI can also use reinforcement learning to learn from feedback and adjust inventory policies accordingly.

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Sushmita Nath

OTM-GTM Cloud Certified Consultant| | WMS | Supply Chain Management | BI| Logistics |Analytics| ML| Python| Data Analysis with Python| Data Science, AI Enthusiast
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AI can automatically trigger stock replenishment based on real time sales data, inventory levels and demand forecasts.This ensures that business maintain optimal stock levels avoiding stockouts or overstock situations. Can predict changing demand patterns based on customer's activities...likes and dislikes, reviews . Automated inventory checks.Amazon, Walmart, Coca-Cola,Zara, Nestle,Ocado already have it in place.

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3 Logistics planning

Logistics planning is the process of designing and executing the transportation and distribution of goods or materials in a supply chain. Efficient logistics planning can reduce costs, improve customer service, and enhance sustainability. However, logistics planning can be complicated by factors such as traffic congestion, route changes, vehicle breakdowns, and delivery delays. AI can improve logistics planning by using natural language processing to process and extract information from various sources, such as invoices, contracts, emails, and GPS data. AI can also use optimization algorithms to find the best routes, schedules, and modes of transportation that minimize time, distance, and emissions.

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Sushmita Nath

OTM-GTM Cloud Certified Consultant| | WMS | Supply Chain Management | BI| Logistics |Analytics| ML| Python| Data Analysis with Python| Data Science, AI Enthusiast
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With the help of AI, it would be easier to get the idea on different lanes,rates based on data and will be able to propose proper solution from it in no time.Basically whatever is the requirement for that lots of time is investment in Data analysis,AI can minimize that time.May be AI would be able to propose a solution.

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4 Quality control

Quality control is the process of ensuring that the products or services delivered by a supply chain meet the standards and expectations of the customers. High quality can increase customer satisfaction, loyalty, and retention. Low quality can damage reputation, increase costs, and lead to legal issues. Quality control can involve inspecting, testing, and correcting defects or errors in the products or services. AI can improve quality control by using computer vision to detect and classify defects or anomalies in images or videos of the products or services. AI can also use anomaly detection to identify and alert deviations or outliers in the performance or behavior of the products or services.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can AI improve supply chain efficiency?

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1 Demand forecasting

2 Inventory optimization

3 Logistics planning

4 Quality control

5 Here’s what else to consider

Computer Engineering

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How can AI improve supply chain efficiency?

1

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1 Demand forecasting

2 Inventory optimization

3 Logistics planning

4 Quality control

5 Here’s what else to consider

Computer Engineering

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