Transforming Supply Chains with Artificial Intelligence (AI)

Businesses must have a supply chain strategy that corresponds with their business strategy. Depending on how a business decides to compete with the market, their supply chain is what will ultimately support that decision.

What is supply chain?

Supply chains consist of all the steps involved in getting a product from the raw material into the hands of the customer.

The supply chain begins with the vendors or suppliers, these are the businesses that provide raw materials.

Next in the supply chain is manufacturing. Manufacturing is the process of converting raw materials into products that are ready to sell.

The final step is distribution which can involve multiple different intermediaries, the intermediaries could be wholesalers, retailers, distributors, and even the internet.

The supply chain consists of different stages which are referred to as upstream or downstream. Upstream operations are those in which the materials flow into the Organization while downstream operations are those in which materials (mostly in the form of finished products) flow away from the organization to the customers.

Similarly, the term logistics is used when talking about a business’s supply chain. Inbound logistics are related to the upstream activities and include all of the movement of the product before manufacturing.

They involve receiving materials, storing them, and the manufacturing processes required to produce the product. Outbound logistics are related to the downstream operations involving just about all of the movement of the product once it is finished.

The supply chain is made up of different processes that work to create a product, these processes lay the groundwork for where a company decides to add value.

The value chain is what gives a business a competitive advantage over others. The more value that is created, the more a customer will want a product and therefore the more profit a company will make.

General challenges with supply chains

1. Globalization

One of the biggest challenges that companies are facing now is how to reduce their supply chain cost. In order to satisfy customers price expectations, companies have opted to relocate manufacturing to low-cost countries around the world in an effort to reduce direct and indirect costs and to minimize taxes.

But having global suppliers contributes significantly to the complexity that comes from extended delivery lead times.

Shipping the products takes a lot of time and customers not only want lower prices but they also want their products on time.

2. Customer Preferences

Global supply chains are complex, combine it with product features that are constantly changing and the challenge is even greater.

A product is released and customers rapidly pressure companies to come up with the next big thing.

Innovation is important since it allows companies to stay competitive in the market, but it’s also a challenge. To enhance a product, companies have to redesign their supply network and meet market demand in a way that’s transparent for customers.

3. Customer Service

Dealing with customer demands is another challenge all businesses will face. Automation is one solution that makes this responsibility easier, as well as improving shipping times, reducing fees and providing faster and accurate order fulfillment.

Customer service can improve with the use of artificial intelligence in the supply chain industry, but it can be expensive.

Ways in which Artificial Intelligence (AL) and Machine Learning (ML) are used in optimising Supply Chains

Artificial Intelligence (AI) and Machine Learning (ML) are already enhancing consumers lives and it has now picked up momentum in supply chain and logistics industry.

In the last decade, Artificial Intelligence (AI) and Machine Learning (ML) has come roaring out of high-tech labs to become something that people use every day without even realising it. In addition to powering numerous apps and other digital products, AI stands to benefit all industries, including Supply Chain logistics industry and the transport sector amongst others.

Here’s how AI/ML is used in optimising supply chains:

1. AI and ML provide insights into enhancing supply chain management productivity

AI and ML can provide an unmatched analysis of supply chain management performance, which, in turn, helps to determine new factors affecting that performance.

According to a report by DHL a logistics company in the transport sector, Artificial Intelligence combines powerful capabilities of three sophisticated technologies, supervised learning, unsupervised learning and reinforcement learning — to identify important factors and issues impacting the performance of the supply chain.

For example, supervised learning can detect identity fraud and make informed predictions, while reinforcement learning can facilitate real-time decisions by supplying relevant data.

IBM Watson is an example of AI being used to boost insights and productivity in the supply chain.

2. AI and ML Enhanced Customer Experience

Artificial Intelligence changes relationships between logistics providers and customers by personalising them. A great example of personalised customer experience is DHL Parcel’s (logistics industry) cooperation with Amazon.

The delivery company offers a voice-based service to track parcels and get shipment information using Amazon’s Alexa-powered Echo.

A customer can query Alexa to find out the current whereabouts of their shipment by asking “Alexa, where is my parcel?” Or “Alexa, ask DHL where is my parcel.”

If there is a problem with the shipment, Echo users could also ask DHL for assistance and be redirected to the customer assistance department of the company.

3. Machine Learning-based algorithms are the foundation of the next generation of logistics technologies

McKinsey predicts Machine Learning most significant contributions will be in providing supply chain operators with more significant insights into how supply chain performance can be improved, anticipating anomalies in logistics costs and performance before they occur.

Machine learning and AI-based techniques are the foundation of a lot of next-generation logistics and supply chain technologies now under development.

The most significant gains are being made where Machine Learning can contribute to solving complex constraints, cost and delivery problems companies face today.

Machine Learning is also providing insights into where automation can deliver the most significant scale advantages.

Prepare for the transformation

The enthusiasm for AI is well founded and the value, while lacking in some areas, is evident in other areas(like pattern recognition and Machine Learning).

The technology already plays a significant role in the transport sector and logistics industry, by increasing effectiveness, efficiency and automating many tasks for supply chain managers and planners.

The recent technological breakthrough in big data, algorithm developments, and ever-increasing processing power, there is a more than likely chance we will get to see an explosion of AI technology driving more sophisticated solutions in the supply chain to speed and improve the delivery of products and services to customers.

Companies relying on manual methods and simple software solutions will not be able to keep pace with their more sophisticated competitors.

Artificial Intelligence and Machine Learning could well be a deciding factor in many industries, determining supply chain superiority, driving customer service excellence and continually improving operational efficiency.

If you want to get ahead of the competitors, then these are things you must do:

• Get informed: If you ever want to get ahead, you should get all the information necessary on Artificial Intelligence and Machine Learning
• Get consulting: Get expert advice on the usage of AI and ML from industry experts.
• Get ahead of the competition by incorporating AI and ML at the early stages.

Logistics and supply chain managers should pay close attention as more AI and ML enhanced solutions emerge.