Use cases of AI in Supply Chain

The supply chain is a diverse and complex domain, and manufacturing industries must align with its workflow to remain competitive. Highly calibrated competencies are required to sync and manage multiple activities during warehouse management, inventory management, and product delivery. Even a small technical glitch and machine downtime can cost you billions of dollars in revenue loss and time to fix the issue on time.

But technology appears to transform the way the supply chain is managed. Today, the explosion of data is a high time. And it is fast, keeping pace with various industries. Artificial Intelligence and Machine learning together have long contributed to digital transformation in the supply chain. According to experts, these two phenomena are expanding their boundaries to offer more tangible use cases in the coming years.  Experts believe they are highly competent to deliver high performance and drive real business results for supply chain management.

AI adoption in the Supply Chain in the coming years

The scope of AI is ever-expanding, and it is triggered by the evolution ofthe new digital era. 

Exploring the latest enablement by AI in the supply chain

As we go further in searching for potential use cases of AI, we have come across the latest findings below.

Predicting Customer’s Behavior

Customers are whimsical. They may step back from purchasing even if the order is about to be delivered. This makes your logistics put up a huge workload and time is wasted. This volatile order pattern can lead to miscommunication between your team and loss of unnecessary productivity loss. More often, an unstable customer behavior is hard to predict due to a surplus of orders from the online retailers.

Hence, the predictability of volatile order volumes is a challenge for many companies. But, AI and ML give freedom to predict the volatile nature of the customer behavior much earlier at an optimal level during such situations. This way, you can avoid time waste and reduce manual errors to invest more resources in business improvement.

Sensing Market scenarios

Observing the market patterns and their behavior is a key to remaining in the business and offering better service to end-users. AI is capable of harnessing real data from external causal resources such as weather, industrial production, and employment history.

As it processes the data from these sources, this application can better gauge the market conditions and assess the growth drivers.

Leveraging its sensory competencies, AI can reshape the capabilities of the supply chain by improving capital expenditure and product portfolio.

Mitigating the risk of chargeback

It is customary to demand a chargeback from brand owners in case of a delay in the delivery of products. As a result, brand owners have to pay hefty penalties for missed On Time in Full deliveries.

With access to advanced AI integrated with deep learning, it is easier to sift through essential data involving the number of orders placed, order types, locatio,n and type of shipment. This helps unearth the real cause of chargebacks while reducing disputes among peers. On the other way around, it is helpful to analyze the cause of failure.

Increasing Fleet efficiency

In the supply chain, on-time product delivery to the destination matters the most. It takes just a minute to make or break your credibility towards winning a customer's trust.

However, it is always unpredictable what is ahead on the route while it is en route to delivery. In such a scenario, an AI-driven GPS tool enables better optimization and navigation of the route for your fleet. It helps you access the most efficient route for product delivery by processing customer, driver, and vehicle data using machine learning.

As a result, it is possible to cut through the most trafficked areas and uneven road conditions. Simultaneously, it helps you save time, money, and reduce the wear and tear of your truck tires. As per reports, it is believed that using such advanced AI-enabled GPS for supply chain delivery, you can save an estimated $50 million per year.

Increasing accuracy in tracking of arriving and departing orders

It is essential in the supply chain to track the path of the order so as to keep the warehouse loaded with fresh product lines.  As manual errors are likely during the path of order arrangement, pallets cannot be positioned properly. Items not moved for long in the warehouse are pushed further back and replaced with the fast-moving items. This can be a challenge for retailers in not putting older products out of the warehouse. AI algorithms can predict the arrival and departure of the product in and out of the warehouse more easily. This is useful in assisting employees to put the pallet in the correct order and release product as per their shelf life.  Companies can become smarter using AI in their supply chain.

With the ever-increasing volume of cloud and AI algorithm intelligence, the supply chain is on the verge of digital representation. Challenges are there as they still adjust to their existing infrastructure. But, if you are really keen to render a real-world platform and predict business challenges, AI can boost your operational goals. With AI-driven decision making, businesses can gain unprecedented speed and scale its business amid the continuous market shifts.  We at Synergylabs take care of your priority and do exactly what fits your domain. Connect with us today.