Intelligent automation (IA) is a relatively new trend that combines two technologies. Intelligent automation in the logistics industry is still in its early stages. Still, people who explore how to apply it now will be well-positioned to deploy it to support their operations. Here’s a closer look at IA and how logistics professionals could use it.
What Is Intelligent Automation?
The definition of intelligent automation varies slightly across sources. However, it typically combines artificial intelligence (AI) with robotic process automation (RPA).
IBM’s intelligent automation definition includes a third component along with those two. It adds business process management (BPM), which concerns automating workflows to make them more consistent and agile.
Here are some examples of the types of technologies or use cases within those three categories:
Artificial Intelligence
- Machine learning
- Advanced algorithms
Robotic Process Automation
- Attended RPA (User triggers robotic software to start or stop a task)
- Unattended RPA (Able to operate with no human involvement)
- Hybrid RPA (A combination that leverages automation and human knowledge)
Business Process Management
- Compliance and risk management
- Procurement
- Customer data
- Contracts
IBM’s definition of intelligent automation stresses that AI is the most critical component since it acts as the “decision engine” for intelligent automation. Advanced AI algorithms can also enable RPA tools and software to handle more complex tasks.
What Are the Benefits of Intelligent Automation in the Logistics Industry?
Logistics leaders and executives elsewhere can expect numerous payoffs by deploying IA in their organizations. Improved productivity is one of the main benefits since people can often do their jobs more efficiently and with fewer errors. Relatedly, employees can use more streamlined processes to get the desired results faster. Such advantages may be most noticeable when performing tasks like processing invoices. IA can do most of the formerly manual work, allowing humans to focus on higher-value tasks.
IA can also make it easier for logistics leaders to comply with state and national regulations. It promotes better record-keeping by reducing duplication, typos and other things that could contribute to inaccuracies. For example, the IA tool could have built-in checks to flag documents lacking the required information or are otherwise insufficient for required regulations.
Intelligent automation in the logistics industry could also result in more-efficient deliveries, especially since many major brands already use some components of IA to deliver goods faster. Walmart’s Express Delivery service, available for more than 150,000 items, uses AI algorithms to accelerate delivery. People get their products within two hours. Humans must oversee route planning, but IA could send customers emails to tell them when to expect their orders.
Intelligent automation in the logistics industry can also improve customer experiences. One possibility is through chatbots, which can answer straightforward questions as efficiently as humans. A business process automation (BPA) element might help categorize which types of queries people most commonly have. Leaders could eventually rely on that data to improve help documentation on a company’s website.
How Have Logistics Companies Used Intelligent Automation?
It’s still not commonplace for people to use intelligent automation in the logistics industry. Many have one or two of the required elements for IA, but not yet all three. However, many are at least pursuing other kinds of automation. One of the advantages is that it makes labor shortages more manageable and results in a safer working environment. IA and additional types of automation can also help company leaders ensure their employees can do their best work.
Ron Finemore Transport, a logistics company operating in Australia, used intelligent automation to improve how an existing transportation management system (TMS) worked. Before making that change, employees had to manually update the TMS with data from a secondary telematics system. The main benefit of the TMS was that it gave customers real-time data on truck locations. However, workers’ productivity suffered due to the need to input information by hand.
The implemented IA solution featured artificial intelligence bots that put details about each truck’s real-time location into a centralized data warehouse. They then matched that information to specific routes in the TMS.
Another case involved logistics company and freight forwarder Davies Turner. Company officials wanted to use automation to reduce the manual labor associated with answering customer queries. Replying to them often took an especially long time because it involved going to the websites of third-party logistics providers to input parcel-tracking information.
The company pursued automation by launching more than 520 software robots to process customer questions. The bots eventually handled more than 30,000 pieces of data or files per week and about 7,500 executions per day.
These early efforts highlight potential gains even when companies don’t use full IA solutions. Many decision-makers, especially those new to automation and other advanced technologies, may wish to deploy one component of IA before using a solution featuring all three.
Deciding When and Where to Utilize Intelligent Automation for Logistics
It’s not easy to figure out the most appropriate ways to rely on intelligent automation for logistics. However, identifying feasible use cases will become easier as more company executives take the plunge by working with the technology.
For now, logistics professionals can start by identifying the biggest weaknesses and challenges within their supply chains and operations. How might automation make the company more resilient and able to overcome obstacles?
Many decision-makers initially balk at the prospect of using intelligent automation in logistics, often because of the costs involved and the time required to alter processes. However, they should try to have a long-term viewpoint and recognize how the lack of IA in the workflow could make their companies less able to compete in the marketplace.
It’s also worth remembering that not every process is a good automation candidate. Any task with many variabilities or requiring extensive knowledge is too much for current automation technology to handle. Today’s commercial options work best when applied to repetitive work requiring no creativity or advanced knowledge.
Finally, it’s often easiest to utilize intelligent automation by working with a specialty service provider, ideally one with experience assisting people at other logistics firms. They can help clients avoid pitfalls and develop solutions most appropriate for their short- and long-term needs and expectations.
Emily Newton is an industrial journalist. As Editor-in-Chief of Revolutionized, she regularly covers how technology is changing the industry.
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