Where to use GenAI in Supply chain Management?

Supply chain automation has altered the way businesses work today. So, when there was a room filled with people thinking how to better the best, enter GenAI – you could say for some it was time to address the elephant in the room. After all, you will find inundated research on how x% of people are wary about using it for millions of reasons and y% of people willingly opened the front door to it.

So, the old-school decided to use the key and GenZ tried to key in the numbers instead, and the door has finally opened for GenAI to enter the supply chain world.

Generative AI and SCM use cases

Generative Artificial Intelligence is the use of artificial intelligence to generate or create something new, so where can newness be added in the supply chain or supply chain management?

I am a math atheist, but I think supply chain can be raised to the power of 10 with GenAI. Supply chain management (SCM) involves manufacturing, distribution, and transportation of raw material and finished commodities.

Let’s first look at it from a simple supply chain angle and then move on to the supply chain management angle.

Fig: Supply chain lifecycle

Fig: Where to use GenAI in Supply chain Management?

Procurement and Generative AI

Raw materials are the first step in your supply chain, although the process is a cyclical one. AI-guided buying will soon become a norm by leveraging advanced analytics and conversational AI. From purchasing being considered an altogether separate function to having GenAI-based systems, and risk evaluation tools, proactive sourcing has become a key. GenAI comes in handy especially when involved in creating processes, documents, and invoices to empower organizations and improve decision-making.

There are some questions that Generative AI can help you answer especially when it comes to procurement.

You ask, GenAI answers: What are the events that can impact my procurement costs? Can you categorize my spending? How do I leverage complex automation? Give me actionable insights looking at my organization’s historical trends, supplier performance, and demand.

Supplier Management and Generative AI

All of us have been privy to ’Pactum’s brilliant negotiation skills with suppliers. Almost two-thirds of people questioned in research preferred to negotiate with a bot as opposed to humans. When leveraging Generative AI for supplier management – areas like supply risk management, supplier communication, contract analysis, monitoring of supplier interactions, and improvement of relationships become simplified.

Training your models to answer some questions that worry you the most can surely be helpful.

You ask, GenAI answers: Help me evaluate identify potential patterns and trends to supplier risks. List some proactive steps I can take to mitigate these risks.

Manufacturing and Generative AI

Training models on large sets of data, leveraging it for factory automation, or even lifecycle management of a product is a good way to boost the efficiency and productivity of those involved in shipping and purchase activities.

Working on aspects of product design by utilizing GenAI to rapidly generate alternative designs can help quicken the ‘ideation’ phase for any product. Asset maintenance is another thing where generative artificial intelligence can come in handy, especially with predicting premature equipment failures or repairs and replacements.

Maintaining or even product design for that matter can be a dollar-spewing affair and labor-intensive too. Some questions that you can get GenAI to help you answer.

You ask, GenAI answers: Help me develop an asset maintenance plan. Give me the most appropriate maintenance schedule – factor in use of equipment, costs, and production requirements. Simulate a maintenance scenario and evaluate the impact of maintenance strategies on overall operational efficiency. Predict the purchase orders that could be impacted by supply risk events. Show me a real time view of when shipments are set to arrive at my warehouse.

Distribution and Generative AI

For distribution and retailing thereafter, inventory is everything. Maintaining an optimum inventory level becomes crucial especially when the finish line is a customer’s hand or home. By involving GenAI to go out on all limbs for this is a good place to start. Analyzing demand patterns to reduce carrying costs and excess inventory through AI algorithms can help any warehouse seem well managed. In the tug of war between demand and supply, you never want the rubber called inventory to snap, so increasing order fulfilment through generative AI can revolutionize the way product inventory is looked at.

In all of this you obviously need to ask the right questions and get the right answers out of your AI model, some questions you can ask them as you train them could be:

You ask, GenAI answers: Are there orders that impacted my supply? Are there shipments in real time that could go outside the customer delivery window? Is there too much demand and will it impact my forecast? Are my forecasts aligned with all the needs of both my partners and customers? Predict the possible disputes I could face when inventory handling.

Logistics and Generative AI

I think if you ever want to learn about the intricate world of supply chains, video games can be a great teacher, there is one game called The Colonists, that takes you the next level of transportation – instead of shipping your raw materials halfway across the colony you decide to establish a manufacturing unit closer to the point of origin. Logistics, this shows if it can get more intelligible will help you build super-efficient and a much lighter on the pocket supply chain. Using Generative AI to optimize transport pick up and drop routes, especially last mile delivery, or analyzing trade agreements.

So, what kind of questions can GenAI answer for you when you begin training your model?

You ask, GenAI answers: Calculate the most efficient routes for my products in real-time by using the current traffic and weather conditions.

Supply chain planning and Generative AI

Generative AI they say is simple, helping you find answers in the easiest way possible. So, when it comes to supply chain planning, simple always works best. Demand forecasting or anomaly detection two, I think great use cases that work like a charm with GenAI. Analyzing historical data and market trends to create demand models. It surely will help in learning from the patterns and then predicting the aftermath ahead of time.

Planning is all about end-to-end visibility, what makes it even more accurate is autonomous planning. Factor in the demand automatically into all the processes at various intervals throughout the chain – inventory, production planning, procurement.

Put simply, traditional planning is a step wise approach. It is mostly restricted by budgets and capacity and acts as a thin link between demand and supply. Profit optimization doesn’t seem to figure here.

Autonomous planning, where GenAI can be leveraged means you use market insights and predictive analytics to ask a lot of questions.

You ask, GenAI answers: Product Y is yet to reach the market and I am yet to get any orders, use the historical data provided to foresee its demand and show me how high the demand. Chart a plan to optimize the inventory in warehouse B. I am looking for a 10 percent reduction in inventory levels and costs. What if there are unforeseen events? Will my forecasts be impacted by these events? If yes, then by how much?

Supply chain and Generative AI is not just meant to change the way data analysts approach it. Generative artificial intelligence is a gift that can touch lives for each person involved in there right from truck drivers to shipping and receiving clerks, purchasing managers, industrial production managers, transportation, storage, and distribution managers. So, it is time to think more about what you can do with GenAI and what GenAI can do for you!

Reach out to us today, to learn how you can introduce GenAI into your supply chain software products.