Companies are saving time, trouble & money by utilizing artificial intelligence in logistics & supply chain management. Learn 5 ways to win.
Artificial intelligence is transforming logistics and supply chain management in numerous ways, helping companies save time and money, while providing better value to their customers.
By processing reams of data and providing optimized solutions, AI is ensuring that cargo moves from point A to point B with minimal complication. Here are five ways that artificial intelligence is improving logistics and supply chain management.
Route Optimization Is Saving Time and Money
Increased use of sensors and other tracking technology allows real time information on the whereabouts of cargo. By combining this information with other factors, such as traffic patterns, weather, and construction, superior routes can be constructed, potentially saving companies both time and money.
Since traffic levels at docks and warehouse bays can change from minute to minute, companies are well served with dynamic decision making capabilities. By combining information on current ground conditions with historical data, AI can deliver useful information, even advising drivers on matters such as refueling, resting, and parking.
Furthermore, AI is empowering autonomous cars and drones, reducing labour costs in the process.
In addition to informing short term logistical decision making, AI is enabling companies to form comprehensive long term strategies regarding the placement of warehouses, or the degree to which air, land, or marine logistics should be relied upon.
Predictive Maintenance is Minimizing Downtime and Costly Repairs
To update a historical idiom, the modern school of thought suggests that if it ain’t broke, you should go ahead and fix it. Artificial intelligence is able to predict breakdowns in vehicles and other machinery before they happen, allowing critical downtime to be avoided, or at least minimized.
The Internet of Things has enabled the collection of a multitude of data points, from tire pressure to general wear and tear. Once again, real time information is paired with historical data to predict potential issues in advance.
Murphy’s Law dictates that problems that are not addressed proactively will surface at the worst possible moment. Customers who are impacted by untimely breakdowns will seek alternate logistical solutions, perhaps never to return.
A truck being tuned up in a service bay at a time when capacity allows for its absence from the road is a vastly preferable situation to a roadside service call during a peak period. Artificial intelligence is guiding this process with ever-increasing accuracy and efficiency.
Demand Forecasting is Improving Inventory Management
Supply chain managers have longed for a crystal ball that would tell them what they’ll need, when, and how long it will take to get it. AI may not be such a tool of clairvoyance, but it’s the next best thing.
Consumer demand is influenced by trends, technological breakthroughs, the competitive landscape, and a host of other factors. Artificial intelligence combines historical data with analysis of news, social media trends, and other inputs to provide a picture of likely future demand levels.
It analyzes supply side factors as well, providing information on likely lead times or potential stumbling blocks. This allows for a more informed procurement strategy, which is good news to those who have been struggling with the ‘just in time’ vs. ‘just in case’ inventory debate that has been a hot topic since the onset of the Covid pandemic.
Human judgement is still a key ingredient in supply chain strategy, of course, but artificial intelligence facilitates the streamlining of data, eliminating the need for dozens of spreadsheets.
Automation is Improving Warehouse Efficiency
Artificial intelligence helps warehouse operators move items through their facilities more efficiently, saving time and labour. Sensors, scanners and barcodes allow for seamless data collection, providing AI with the information it needs to create better routes and retrieval systems.
With the right system in place, order processing, picking, and packing are streamlined, while human error is minimized. Stock control is improved and potential stockouts are flagged. This is particularly effective when used in synergy with the aforementioned demand forecasting capabilities.
Even warehouse safety can be enhanced when AI is given access to safety data, allowing it to assess incidents and flag potential hazards.
AI is Streamlining Last Mile Delivery
Last mile delivery is an important, but expensive, component of supply chain management. The increasing proliferation of e-commerce has not only led to a higher volume of deliveries, but also to more returns, further compounding the challenge.
AI can assess traffic, shipment data, customer-preferred delivery windows and more, leading to better routing and delivery scheduling. Data dashboards allow for information exchange with drivers and real time tracking of key performance indicators. Cameras can even scan loads to ensure better packing. As autonomous vehicles and drones become more and more commonplace, so, too, will AI’s influence.
Technology such as artificial intelligence will continue to shape logistics in the coming years. While nobody can anticipate exactly how these evolutions will unfold, it’s folly to believe that sticking with the status quo will suffice.