by Fronetics | Nov 19, 2019 | Blog, Logistics, Robotics & Automation, Supply Chain
Artificial intelligence is shaping the future of supply chain companies, helping to improve accuracy, speed, efficiency, and more. Here are 4 practical ways for supply chain companies to incorporate AI.
A recent Forbes article focused on how specific supply chain companies are making advances with artificial intelligence. And, with powerful stats like these, it’s easy to see why more and more companies are investing in AI:
- AI technology can enhance business productivity by up to 40%.
- 84% of global business organizations believe that AI will give them a competitive advantage.
- By 2025, the global AI market is expected to be almost $60 billion; in 2016 it was $1.4 billion.
- AI startups grew 14 times over the last two decades.
But after reading the Forbes article, I was left thinking about practical applications for AI within the industry. Here are four examples of how AI can be beneficial to your supply chain.
4 ways artificial intelligence can benefit your supply chain
1) Autonomous vehicles
We’ve all known for many years that driverless trucks have major potential to affect the supply chain. And though we aren’t there yet, if autonomous trucking can be developed to its potential, the technology would allow for faster, more efficient deliveries without the need for drivers.
“Autonomous vehicles are being fitted with cameras, sensors and communication systems to enable the vehicle to generate massive amounts of data which, when applied with AI, enables the vehicle to see, hear, think and make decisions just like human drivers do,” writes Suhasini Gadam for Medium.
As the cost of producing autonomous vehicles drops, the benefits for the supply chain increases. Aside from efficiency, reduced lead time, and route optimization, PwC’s new report shows the digitization and automation of processes and delivery vehicles will reduce logistics costs for standardized transport by 47% by 2030.
2) Final-mile delivery route efficiency
Route optimization software and AI-powered GPS tools are making their mark. And for good reason. Big-names like Amazon have left smaller businesses clamoring to keep up with their efficiency. In fact, Amazon is predicted to account for 50% of the entire e-commerce retail market in the U.S. by 2021.
AI is helping smaller brands compete with larger corporations by producing cost-effective technologies that end in lower overhead costs and higher quality customer service. AI provides prediction on delivery quantities, locations, and patterns for optimal delivery routes, including road conditions and other factors.
3) Demand forecasting
Machine learning has the ability to quickly identify patterns in supply chain data by relying on algorithms to find the most influential factors. The ability for machines to find data patterns without human intervention has applications across the supply chain.
In an interview with Forbes, Dr. Michael Feindt said:
“To help companies draw the right conclusions from the data they gather, businesses need to apply ML and AI technology designed to grasp the oncoming impacts of what’s happening everywhere in the moment and predict how demand and supply will look in the future. That means having algorithms that can evolve over time.”
AI makes it easier for brands to identify patterns in their supply chain and forecast the needs of their business to make internal processes more efficient, eliminate costs, and reduce loss of goods. The ultimate goal of AI is to forecast demand without excess production.
4) Chatbots for marketing and operational procurement
Chatbots are AI computer programs designed to conduct conversations, simulating how a human would interact. The program communicates with customers inside messaging apps, like Facebook Messenger.
Chatbots are relatively inexpensive, inherently low-maintenance, and surprisingly user-friendly — to both the buyers interacting with them and the vendors setting them up. They help website visitors find the information they need quickly, while gathering user data that is useful in marketing and sales efforts, all without taxing human resources. In fact, Chatbots Life reports that businesses can save up to 30% of costs associated with servicing customer requests by using a chatbot.
How is artificial intelligence impacting your supply chain?
Related posts:
by Elizabeth Hines | Mar 20, 2019 | Blog, Logistics, Robotics & Automation, Supply Chain
With the power to drastically increase efficiency in all areas of the supply chain, it’s important brands are exploring the benefits of AI. Here are four examples of how AI can benefit your supply chain.
Highlights:
- It’s estimated that supply chain firms could gain $1.3 to $2 trillion a year from using AI.
- Machine learning has the ability to quickly discover patterns in supply chain data by relying on algorithms and constraint-based modeling to find the most influential factors.
- The increasing popularity of chatbots is making it harder to ignore how AI is helping shape not just the daily logistics but also the B2B marketing landscape and operational procurement for supply chain industries.
Artificial intelligence is not simply affecting supply chain management, it is revolutionizing it.
With the power to drastically increase efficiency in all areas of the supply chain, McKinsey estimates that firms could gain $1.3 trillion to $2 trillion a year from using AI in supply chain and manufacturing.
Here are 4 examples of AI and how it’s changing supply chain management for the better.
1. Autonomous transport
There’s nothing more exciting than the field of autonomous transport for SCM. We’ve all known for many years that driverless trucks have major potential to affect supply chain management and logisitics.
We aren’t there yet – and “anyone employed as a driver today will be able to retire as a driver” — but if autonomous trucking can be developed to its potential, the technology would effectively double the output of the U.S. transportation network at 25 percent of the cost.
The conversation is no longer simply talking about vehicles on the road either. Google and Rolls-Royce recently partnered to build autonomous ships too.
2. Final-mile delivery route efficiency
One doesn’t have to have a driverless vehicle, however, to use AI to optimize delivery logistics.
For example, in the “devilishly complex” task of delivering 25 packages by van, the number of possible routes adds up to around 15 septillion (that’s a trillion trillion).
That’s where route optimization software and AI-powered GPS tools like ORION — which UPS uses to create the most efficient routes for its fleet — are making their mark. With ORION, customers, drivers and vehicles submit data to the machine, which then uses algorithms to creates the most up-to-date optimal routes depending on road conditions and other factors.
And there are also other autonomous entities out there besides cars, trucks, and ships. Robots using LIDAR technology are now being used to deliver items in crowded city environments. For example, Marble’s robots deliver medicine, groceries, and packages, and they also track their routes and the condition in order to continuously improve delivery for the next time. Additionally, last-mile solutions with drones continue to be explored due to their ability to move quickly and bypass almost all ground-level obstacles.
3. Demand forecasting, particularly for warehouse management and SCM strategy
Machine learning has the ability to quickly discover patterns in supply chain data by relying on algorithms and constraint-based modeling to find the most influential factors. This ability to find data patterns without human intervention has applications in EVERY aspect of SCM, but demand forecasting is a particularly influential component beneficiary.
Warehouse management and SCM strategy rely heavily on correct supply, demand, and inventory-based management. Forecasting engines with machine learning offer an entirely new level of intelligence and predictive analysis of big data sets that provides an endless (and constantly self-improving) loop of forecasting, overhauling the way we manage inventory and the way we create new strategies for our industries.
4. Chatbots for marketing and operational procurement
The increasing popularity of chatbots is making it harder to ignore how AI is helping shape not just the daily logistics but also the B2B marketing landscape and operational procurement for supply chain industries.
A chatbot is a computer program that simulates human conversation using auditory or textual methods. It communicates with your customer inside a messaging app, like Facebook Messenger, and is similar to email marketing without landing in an inbox. Mimicking a human conversation, chatbots currently allow for increased customer engagement through messaging app technology that isn’t yet saturated with marketing. They are just one of the many ways to integrate AI and marketing.
There’s so much more than these 4 examples to consider when discussing AI and the supply chain: prediction of delivery arrival times to the warehouse and to the customer, cargo sensors, automated purchasing, financial applications…the list literally may be endless.
Choosing what to focus on for this article, and more importantly, for all supply chain and logistics businesses, is a tough decision, but one thing is clear: in the “arms race” to leverage AI in SCM, some will come out on top and some will be left behind.
This post originally appeared on EBN Online.
Related posts:
