New technologies have the power to streamline supply chains at every level — and it’s already being put to work.
Artificial Intelligence (AI) is somewhat of a buzzword right now. However, where these tools make headlines in areas like self-driving cars and chatbots, their ability to learn from experience, adjust to new inputs, and perform ‘humanlike’ tasks has made them an attractive prospect to many industries — including the supply chain.
In a study by Gartner, leading supply chain organizations expect the number of AI and machine automation projects to double over the next five years. Recent evidence from those employing the technology supports this move as well, with one study finding that supply chains with AI-powered capabilities are over 65% more effective, with reduced risk and lower overall costs, while additional research shows that 53% of executives report increased revenue, and 61% report decreased costs as a direct result of introducing artificial intelligence into their supply chains.
So how is this technology being applied in supply chains? Below we outline the top 3 areas where it’s already having an impact.
1. Enabling precise inventory management
Existing warehouse management systems are often slowed down by inconsistent, inaccurate, and outdated information. Costly practices like overestimating demand to ensure availability means that in 2019, retailers were sitting on around $1.36 of inventory for every $1 in sales. On the other hand, additional studies have shown that 34% of businesses ship late because they mistakenly allow purchasing of items that are out of stock.
Costly miscalculations like these can happen all too easily when leveraging manual processes that leave room for human error. However, with their ability to analyze large volumes of data quickly, AI driven tools can prove to be highly effective at tasks like inventory management.
By quickly analyzing and interpreting huge datasets, much of the guesswork can be removed from inventory optimization. The ability to instantly deliver alerts on low inventory, delivery delays, underperforming areas, and incidents as they occur, it can play a huge role in improving speed, efficiency and accuracy of your inventory management systems.
Going one step further, AI systems can also be put to work to predict new consumer habits and forecast demand. By analyzing data on historical sales, seasonal fluctuations, abnormal demand patterns, promotional plans and other contextual information, it’s possible to generate highly accurate demand forecasts.
2. Adapting to supply chain volatility
Supply chains have always been susceptible to unpredictable volatility. Natural disruptions like hurricanes in Florida and snowstorms in Texas, along with others like trade wars and labor disputes are all too familiar. And today, all of these have been further exacerbated by the COVID-19 pandemic, elevating the need for agility and flexibility to new heights.
The problem with issues like these is that they don’t occur with enough regularity for supply chain managers to track and predict them in advance. However, by bringing AI capabilities to your supply chain, it becomes possible to discover insights that can help to minimize the level of disruption they cause, and in many cases, stay ahead of the disruption entirely.
For example, when wildfires shut down transportation through a certain route, it can quickly identify and divert shipments along an optimized detour and proactively notify the shipper and customer. Likewise, when projected loading times are affected by events like labor shortages at a certain port, it can quickly identify this and provide alternative options that will get your shipment to its destination faster. Weather data can also be integrated with operational data to actively predict potential problems and establish a best course of action for supply chain managers to take to avoid disruption.
3. Optimizing last mile deliveries
With their direct impact on the customer experience, last mile shipments are often considered to be the most important element in the supply chain. What’s more, according to a report from McKinsey, it also comprises as much as 50% of the overall shipment cost, making it all the more important to ensure timely delivery.
This pressure is what has caused many companies to turn to AI powered systems in their quest to reduce transportation costs while meeting customer expectations. By taking in huge amounts of operational data, an AI powered system is able to learn the inner and outer workings of the business and make route optimization recommendations in real time.
Able to provide accurate information and guidance on the optimal number of vehicles required and the most efficient route to be taken to deliver the packages to each location on time. And since AI is continuously learning, the system can analyze and refine those routes on an ongoing basis, adapting to changes that could otherwise be missed.
When brought to route optimization, AI has the power to make logistics operations more efficient and cost effective, while also improving the customer experience.
How to put AI to work in your supply chain
No matter how you bring AI capabilities to your supply chain, there are still people behind the desks, at the wheel, and in the warehouses who need to be able to put those capabilities to work. The benefits outlined above mean nothing if the people using them can’t easily take advantage, so any solution has to be capable of fitting into the way they work in order to deliver results. So how can this be accomplished?
1. Bring all of the issues onto a single screen
Supply chain managers are typically already burned out by having to navigate multiple platforms, screens, windows, and tabs, which makes it incredibly difficult to spot issues as they arise. All the information in the world can’t be useful if it’s difficult to find, so adding an AI solution to the mix should serve to make that information as easy to utilize as possible. By having all issues across the supply chain organized and available at a glance on a single screen, it’s impossible to miss an important update.
2. Provide the ability to take instant action
Employing AI to seek out and identify issues in the supply chain is the first step toward addressing them quickly. Take that a step further and it can also help to solve them while eliminating human error and guesswork from the equation. The same ability to identify issues can be utilized to understand what solutions may be available to correct them. Sometimes an automated approach may be best, or when human intervention is required, the system should be capable of presenting options, as well as the ability to take action on them instantly.
3. Set limits to the data presented
AI creates data — a lot of it. And as valuable as it is, having to scroll through pages and pages of information that isn’t relevant to your job is more likely to create more frustration than efficiency. Allow those with access to the data to cut through the noise and focus on the specific supply chain issues that they want to view with customizable filters. Whether that’s time periods, regions, shipment types, or their own top priority shipments, the data can only be useful if it’s useful to the person viewing it.
Properly implemented, AI has the power to break down the silos that exist in current supply chains, providing true end-to-end visibility and increased efficiency across the whole supply chain operation. To examine how three Shipwell customers put AI to work in addressing their own unique supply chain issues with our new Compass Dashboard capabilities, download our white paper now: Keeping your supply chain on track: How AI is streamlining exception management
Discover how AI is changing exception management
Uncover the ways that new advancements in issue tracking and management have empowered supply chain managers to increase visibility, address issues faster, and stay focused on what matters — and how you can do the same.