Leveraging AI for improving efficacy of Supply chain & Strategic Management

The global supply chain is filled with several variables that add to its complexity: government regulations, ever-changing customer demand, rising transportation costs, and international events such as pandemics. Any innovation that helps improve the supply chain’s efficiency can help increase your bottom-line profit.

Artificial intelligence (AI) is one such innovation that helps optimize the supply chain by better forecasting customer preferences and cutting costs by automating some repetitive manual tasks.

Businesses can leverage artificial intelligence (AI) to optimize their supply chain management by enhancing efficiency, visibility, accuracy, and decision-making across various supply chain processes. Here are several ways AI can be applied to achieve supply chain optimization:

Demand Forecasting: AI can analyse historical data, market trends, seasonality, and external factors to predict demand more accurately. This helps reduce inventory holding costs and minimize stockouts.

Inventory Management: AI algorithms can determine optimal inventory levels by considering demand, lead times, and supplier performance. This prevents overstocking and understocking issues.

Supplier Management: AI can assess supplier performance based on factors like on-time deliveries, quality, and compliance. It helps identify reliable suppliers and minimize disruptions.

Supply Chain Visibility: AI provides real-time visibility into the entire supply chain, allowing businesses to monitor shipments, track inventory, and respond to disruptions promptly.

Risk Management: AI analyses data from various sources to identify potential risks and disruptions, enabling proactive risk mitigation strategies.

Order Processing and Fulfilment: AI-driven order processing systems can automate order routing, allocation, and fulfilment, reducing manual errors and improving order accuracy.

Supplier Collaboration: AI-powered platforms facilitate collaboration between suppliers and buyers, enabling efficient communication, order updates, and demand sharing.

Quality Control: AI can be used for quality control by analysing data from sensors and cameras to identify defects or inconsistencies in products.

Optimizing Lead Times: AI algorithms can analyse historical data to optimize lead times and delivery schedules, ensuring products arrive when needed.

Sustainability and Environmental Impact:   AI   can help identify opportunities to reduce carbon footprint by optimizing transportation routes, minimizing waste, and improving energy efficiency.

Price Optimization: AI algorithms can analyse market data and trends to optimize pricing strategies for products, considering factors like demand and competition.

Customization and Personalization: AI enables the customization of products and services to individual customer preferences, enhancing customer satisfaction.

Real-time Decision-Making: AI provides data-driven insights in real-time, enabling supply chain managers to make informed decisions quickly.

Continuous Improvement: AI analyses performance data over time to identify patterns and areas for improvement, helping optimize processes iteratively.

Route Planning and Optimization- AI-driven route planning and optimization tools consider factors like traffic, weather, and delivery constraints to find the most efficient routes, reducing transportation costs and lead times AI can optimize transportation and logistics operations by analysing real-time data on factors such as traffic conditions, weather, and delivery schedules. With these factors, AI can minimize transportation costs, reduce delivery times, and enhance customer satisfaction.

Warehouse Management &   Automation –  AI- powered robotics and automation can optimize warehouse operations by handling tasks like picking, packing, and sorting, improving speed and accuracy AI-powered robots and automation technologies can improve the efficiency and accuracy of warehouse operations. AI   algorithms can optimize inventory placement, automate picking and packing processes, and enhance overall warehouse productivity, leading to faster order fulfilment, reduced labour  costs, and improved operational efficiency.

Automation can help with the timely retrieval of goods from the warehouse and facilitate a smoother fulfilment of orders. As you keep purchasing inventory, the algorithm continues to learn from the data, and – based on this purchase and supplier data – the AI can provide stocking recommendations.

Lack of real-time information can lead to inefficient warehousing. Using a warehouse management system can offer much needed clarity and help in streamlining your operations. A warehouse manager can get real-time insights about the various parts, components, and finished inventory stored in the warehouse, since the technology takes virtually no time to process and analyse large swaths of data.

Drones are also helping to automate warehouse operations. In movies and wedding ceremonies, drones are often used for videography from a higher altitude. At the warehouse, drones scan and capture information from barcodes and RFID tags, as well as reconcile data with your warehousing software. Apart from scanning, the drones can also pick up inventory and aid with quicker shipping. Using drones to fetch items from higher shelves also mitigates the risk of warehousing staff injuries caused by falling from height.

Supplier Management – AI can streamline supplier selection and evaluation processes by analysing supplier performance data, quality metrics, pricing information, and other relevant factors. By identifying the most reliable and cost-effective suppliers, AI can help improve supplier relationships, reduce risks, and enhance supply chain resilience.

Green Initiatives – AI can support sustainable practices in supply chain management by optimizing transportation routes to reduce carbon emissions, identifying energy- efficient processes, and facilitating waste reduction and recycling efforts. By promoting sustainability, AI can help companies meet environmental goals.

Predicting trends – It can be challenging to plan for the supply chain due to globalization, competition, increasing product varieties, and varying customer preferences. Unplanned events such as pandemic-related lockdowns and logistical issues can fuel the fire.

When final production relies on the timely availability of several spare parts and critical components, their unavailability can create bottlenecks in the supply chain. With a robust AI-powered forecasting system, businesses are equipped with the necessary intelligence to prepare themselves before such events disrupt production.

Along the lines of AI, there is a buzzword called “Big Data” that is commonly used. As the name suggests, Big Data refers to data that is huge in volume and keeps compounding over time.

To effectively implement AI in supply chain management, businesses need to invest in the right AI tools, data infrastructure, and expertise. A holistic approach that combines AI technologies with domain knowledge and human expertise is essential for achieving successful supply chain optimization.

AI will certainly be a focus area to improve supply chain management. Adapting to technology will be crucial for businesses to stay ahead of the competition.

AI can be used to improve supply chain management and logistics for several reasons:

1. Improved Efficiency: This can help businesses to optimize their supply chain operations, reducing costs and improving efficiency.
2. Cost Reduction: By optimizing routes, inventory levels, and supply chain risks, businesses can reduce their costs, enabling them to improve their bottom line and reinvest in other areas of their business.
3. Enhanced Customer Satisfaction: This can help to improve customer loyalty and retention, providing a competitive advantage in the marketplace.
4. Better Decision-Making:  By leveraging the power of AI, businesses can make data-driven decisions that are based on accurate, real-time data.
5. Scalability: This makes it an accessible and affordable option for businesses that want to improve their supply chain management and logistics.

AI offers numerous benefits for supply chain management and logistics, including improved efficiency, cost reduction, enhanced customer satisfaction, better decision-making, and scalability.

Taking this forward, Generative AI creates new content, such as images, text, audio or video, based on data it has been trained on. While the technology isn’t new, recent advances make it simpler to use and realize value from. As investors pour cash into the technology, executives are racing to determine the implications on operations, business models and to exploit the upside. For those who diligently pursue innovation guided by strategy and an understanding of the limitations — not by an impulse to chase after the latest shiny object — generative AI can prove to be an agile co-advisor and multiplier in strengthening supply chains.

Possibilities do exist and already being leveraged in real-world use cases across the end-to-end supply chain. These projects are enabled through generative AI’s ability to:

• Classify and categorize information based on visual or textual data.

• Quickly analyse and modify strategies, plans and resource allocations based on real-time data.

• Automatically generate content in various forms that enables faster response times.

• Summarize large volumes of data,  extracting key insights and trends.

• Assist in retrieving relevant information quickly and providing instant responses by voice or text.

Generative AI adds simplicity to interactions throughout tech- enabled planning efforts.

The “chat” function of one of these generative AI tools is helping a biotech company ask questions that help it with demand forecasting. Company can run what-if scenarios on getting specific chemicals for its products and what might happen if certain global shocks or other events occur that change or disrupt daily operations.

The ISACA (Information Systems Audit and Control Association) survey recently taken reveals that employees based in Asia are using generative AI in the following ways:

• Create written content (67%)
• Increase productivity (41%)
• Customer service (such as chat box) (30%)
• Automate repetitive tasks (28%)
• Improve decision making (23%)

Today’s generative AI tools can even suggest several courses of action if things go awry. Risk management may be the most promising area, particularly in preparing for risks that supply chain planners haven’t considered.

India (Bharat) is already adopted the Tech change with Digitisation to enable business, which makes the Decade ahead of us as “TECH-ADE”