The supply chain is one of the prime elements of every business. Therefore, it should not be taken for granted and has to be streamlined effectively. With the rising market demands and competition, the process of supply chain management can become challenging for businesses. How?
Several aspects, including inventory management, demand forecasting, route planning, etc., are affected due to shifts in market dynamics. As the market data can be in huge heaps, analysis, plan formulation, and execution can take forever.
The perfect solution to unlocking efficiency in supply chain management is utilizing the perfect technology, Generative AI!
Widely popular with the name ChatGPT, the technology has cutting-edge potential and a rapidly growing market ($137 billion by 2030). Let me help you uncover the role of GI in optimizing supply chain management.
A Quick Overview of Generative AI!
Generative is a groundbreaking technology that has transformed several businesses across the world. If I talk about its working, it works a bit differently than the conventional AI.
Generative AI analyzes real-time and constantly changing data to devise insightful results. Unlike conventional AI, where time series analysis, regression models, and other ML algorithms are used, generative AI uses deep learning models to curate content and generate data.
Here are some quick benefits of generative AI!
- Accurate demand forecasting
- Better quality products
- Streamlined operations
- Efficient cost balancing
- Enhanced operational efficiency
Insightful Use Cases of Generative AI in Supply Chain Management!
“Generative AI is the key to solving some of the world’s biggest problems, such as climate change, poverty, and disease. It has the potential to make the world a better place for everyone.” – Mark Zuckerberg.
Not just the founder of Facebook but business tycoons from around the world are speaking in favor of generative AI.
Here, I have compiled some use cases that will help you understand the relevance of the above quote!
- Demand Forecasting
Demand and supply analysis is a critical part of supply chain management. After all, overstocking and being out-of-stock can lead to significant business losses. As per statistics, inventory distortion can lead to losses of around $818 billion per year. The primary share of this is of out-of-stock goods, and the rest is of overstocked goods.
I was stunned by looking at these numbers. To prevent such massive losses, generative AI can be utilitarian.
Generative AI can use a combination of historical data, market shift data, and live external data to tune the precision of demand predictions. Thereby driving operational efficiency and financial benefits. GI can further assist in allocating resources tactically.
Procter & Gamble and Amazon are excellent examples here! Amazon AI algorithms can predict the demand accurately down to the zip code level.
- Route Optimization
Route optimization is more about picking the best route for delivery. It includes assessing factors like fuel costs, customer needs, vehicle capacity, and whatnot. Based on a precise analysis of these factors, route optimization for supply chain management happens.
Generative AI can assist businesses in the assessment of these and several other factors, including traffic patterns, local events, weather forecasting, etc., to reduce delivery time and boost customer satisfaction.
Furthermore, with access to live data, generative AI can also undertake dynamic routing for enhanced efficiency.
UPS, aka United Parcel Service is a package delivery company that uses generative AI to seamlessly optimize delivery routes. To do this, it utilizes data elements, including traffic, weather, and package weight.
- Inventory Management
Inventory management is all about preventing overstocking and out-of-stock scenarios. As I have highlighted earlier, because of over-stocking and out-of-stock products, business losses can go in billions. To avoid such situations, precise inventory management is necessary.
Generative AI can help you place informed inventory orders based on a plethora of factors. Deep learning AI models can analyze real-time demand signals, current inventory levels, supplier lead times, etc., to reduce product shortages, minimize surplus inventory, and lower holding costs.
Walmart is the perfect example here!
Walmart leverages the power of AI in its specialized floor scrubbers. These devices scan the shelves in the Amazon warehouse and look for items that are out of stock or less in stock. Based on the presence of light and depth of the shelf, these scrubbers alert the associates for restocking. The accuracy of these scrubbers is close to 95%.
- Risk Management
What if the market demand is high, but supply is low? There could be scenarios where your suppliers might not be able to fulfill your demands, and you will be at risk of losing your customers. The recent pandemic is the perfect example of this.
In such a scenario, you need to plan in advance, and this can only be done with the help of generative AI. On the basis of geopolitical events, weather forecasting, recent supplier disruptions, and natural disasters, generative AI can help you plan ahead. You can change the supplier temporarily and relocate your inventory to mitigate risks.
Maersk, which is a global shipping and logistics company, has employed generative AI to analyze geopolitical and environmental risks and other factors to minimize chain disruptions.
Final Words
With generative AI, you can amp up your supply chain operations and streamline several other industrial processes. Moreover, with the help of add-on technologies like artificial intelligence, IoT, machine learning, etc., you can completely automate your industrial operations.
If you aim to amplify your business returns, it is time to upgrade your arsenal or the tools used for your business operation management. Generative AI is one of the best upgrades to make right now, and INTECH can help you build a versatile generative AI. Get in touch now!