Businesses constantly seek innovative solutions for their supply chains to streamline operations, reduce costs, and enhance customer experience. Generative Artificial Intelligence (Gen AI) offers promises to fulfill those exact wishes. But can it do just that? I’m going to answer that question for you as well as offer some practical insights into how you should be implementing Generative AI in your supply chain. 

What is Generative AI?

Before we dive into its impact, let’s briefly discuss what exactly is Generative AI. Now, there’s a lot of definitions out there, but here’s how I define it. It’s a system that can create new patterns based on the interpretations of learned patterns. It also comes down to three main components.

Foundational Model

This is where the training/learning takes place, where you’re teaching the AI how to look at things and look at input.

Large Language Model (LLM)

This model is trained on vast amounts of text, can interpret what you’re asking of it, and can put a response in words that you can understand.

Natural Language Processing Model/Chatbot

This is the most visible portion of current Generative AI implementations, like ChatGPT. This model component is generally a conversational chatbot leveraging the LLM to create content. It was first trained on a foundational model and then fine-tuned with human feedback. 

Generative AI is first trained on a foundational model and then fine-tuned with human feedback and additional data.

Now, none of these are really new technologies. They’re just available more widely today because of the lowered cost of processing power, rise in cloud technology availability, and ability to push it out in more cost-effective manners. 10- 15 years ago, it was far too expensive. As prices have come down and processors have become more powerful (think Moore’s Law), it’s allowed Generative AI to become more easily accessible. 

When you talk to Generative AI it feels like it understands you. Spoiler alert, it doesn’t. Its responses are based on data it has consumed and a resultant powerful prediction mechanism. Don’t think that Gen AI “understands”; it doesn’t. This has significant impact when it comes to focusing a Generative AI into a particular industry, like logistics. Generative AI can’t apply specific nuances of an individual industry unless it has been trained on them, and even then, there are other obstacles to Gen AI being useful outside of targeted use cases. This is a key point in how we think of getting Generative AI to effectively impact supply chains. 

Public vs Private Generative AI

When you use Generative AI, there’s a big thing you should be concerned about – public vs. private Generative AI.

Public AI

We talked about ChatGPT. That is one example of a public version of Generative AI. Anything you input in there is being reused for training purposes. Any of the prompts you put in, it’s using that to train itself and feed back into that foundational model for others to use. That becomes more or less public domain once you put it in there. You must think about it that way. It’s like posting something on the internet – it’s there forever. 

Public AI is great to use for idea generation, but only put in anonymized data, that’s if you put in any data at all. 

I also cannot stress this enough – fact check what it generates. Generative AI will make stuff up – the industry term is hallucinations. It’s the worst people pleaser you can imagine. It will give you what you ask for, whether that’s true or not. There are advances in the works to help “fact check” the tool, but you must remember whatever Generative AI does today is opaque. We don’t know where it’s pulling this information from. You’ve got to go in and check its responses.

Private AI

There are opportunities to use private Generative AI. Amazon Bedrock and Microsoft’s OpenAI implementation have private options to use such that the prompts and any data you put in are not used for training the core foundational model. But you must make sure you’re on the right (private) version of the tool. 

The second thing is that if you feed it data, you must make sure that data is right because Generative AI has no clue. It’s assuming what you’re telling it is true. Though it does have the ability to fact check your data, it will only do so if you ask – and ask correctly. You must have clean data and validate the results that come out of it.

Again, private AI is great for idea generation but not so great yet as a fully automated toolset that can be used to drive business forward. It’s getting there, but not there yet. Private AI options will get there faster for certain topics, industries, and businesses than public AI. 

Generative AI Latest Features 

There are some new features that have come out for Generative AI recently. One of those is the ability to relate images and text. You can put an image up, and it can write a story about that image. You can input text, and it can create an image, like Dal-E. 

There’s also code creation and injection. It can generate code, and when I say code, I mean programming. OpenAI has functionality where you can do code injection. Github has its copilot technology where it can write code alongside you based on a plain English prompt. 

Another feature is enables tools to call digital actions. So, I can go from a Generative AI tool and call out to create an action in another application. This is where we shift over into physical actions that we find in Logistics 4.0. For example, a robot in a warehouse that results in a physical action, or it could just be something as small as, if this event takes place, then make this phone call or change this data. 

The Impact of Generative AI in Supply Chain

What’s the logistics impact of Gen AI? Biggest one is data analysis. 

Data Analysis

Generative AI is great at taking data in and putting it into a format that can be easily used to extract meaning. Think about this from a summarization perspective. You’ve got somebody on a call with a customer. Based on their phone number, Generative AI identifies them and comes up with a prompt that tells you the last 30 days of that customer’s history (products, contacts, issues, etc.) so you can have a much more informed conversation with them. 

Trending is another great one to look at across data sets. As you put the data sets in and tell Generative AI to relate these two things, you can start to see trends against each other. It’s interesting what you can do with those pieces.

Then there’s assistive information delivery. At points in time where actions need to be taken, information can be delivered as a prompt to the person performing the action. This can happen in real-time with some tools, or it can happen in the background.

These are all pieces that you can put into place today.

Predictive Analysis

A primary use case within logistics is predictive data analysis. 

Routing is one but that’s going to take some work to be effective. That’s because it needs specific knowledge sets around the model and those knowledge sets are not available to most of generic models. There isn’t a specific logistics model yet that understands all the nuances to the different modes and can bring in the data sets that are necessary to truly understand routing. There are tools you can use for routing right now, but they’re not Generative AI tools.

Exception identification is another one. Again, this is a large data problem and there are a lot of factors that come into it. Any supply chain is essentially a complex system. Being able to identify those exceptions earlier is going to be something Generative AI will help with when it comes to logistics and supply chains.

Hyper-personalization is a great one. That’s getting information into a format that speaks to a particular person, entity, or customer. You can hyper-personalize a piece of communication to them based on the information you know to make sure it’s something you can use to improve service delivery. 

These benefits of Generative AI are really where we’re going to be able to improve service delivery across supply chains as it evolves. 

How to Use Generative AI in Supply Chains Today

You’re likely wondering, how can I use it today? I’m happy to report that there are several different ways you can being using it. 

Improving Customer Experience

One of those ways is improving customer experience. Using a private AI, you can feed it customer data. Then, when you’re talking with customers you can bring up insightful information. It can bring up things like a notice of a customer’s birthday and save you time from having to go and look up specific pieces of information. 

If you’re feeding the data into a system, you can use these private models to intake that data and provide relevant information back to someone that’s interacting with a customer. This is where I like to remind everyone that Generative AI isn’t a replacement for people in customer service but is great for putting information into a digestible format to support people in their roles. 

Summarization

One of the big things is summarization. Summarization is an awesome feature of Generative AI. It’s ability for it to take data and create a summary is a tool that you can use today. Getting summaries of articles, getting summaries of customer history, getting summaries of a lot of different types of data is something the current application can do and do it well. You still have to fact check it, though!

Personalization

The other big piece is the creation of personalization. Getting that data in and creating a personalized email with some information about who you’re sending to is something that Generative AI can do and at scale. There are tools you can use to do that and it’s something that you can put into place today and try out. 

Think About Your Data

I would encourage everyone to get started and try things. It’s not going to be perfect out of the gate. I can tell you that right now. 

One of the key factors that you must think about as we move into this Generative AI world, is data. Good, clean data is at the core of successful AI use. You must think about how clean your data is, what data you’re going to send to an AI, are you public or private, all those pieces. 

Accuracy and consistency are the core. You must establish your data governance. It’s great if you have clean data, but if you start feeding bad data in again, all you’re going to do is skew your results coming out. Now is the time to start evaluating your data sets. Understand where you have good data, how your data is inputted, where you can start, and where you need some work. Then, get your data in line and start to think about how you can enrich that or what can you do with it.

Before You Get Started…

There are other pieces to consider before you fully dive into Generative AI. 

There’s an ethical component here. There’s change that’s coming. People’s jobs are going to be affected. You must think about how this impacts your team. What trainings do you need to provide? How do you get people brought along for this ride instead of leaving them behind? What’s the impact to your customers? If you’re relying on this as an assistive technology, how are you making sure that you’re still servicing your customer effectively? 

One great thing about automation is that it makes things happen in the background. The bad thing about automation is things happen in the background. Unless you understand what’s happening, can react to that, and leverage it to effectively service your customers, you’ll end up doing them a disservice. That’s true for any automation and Generative AI is no exception. 

Then there’s change management. How do you prepare your people? How do you get to the point where you have prompt engineers? 

Each AI works differently. If you give the same prompt to different AI applications, you’ll get different answers. So, how do you understand how to engineer those prompts? How do you identify this skill? These are critical questions you’ll need to answer over the next few years as we move into this Generative AI world. 

FAQs 

Are There Logistics Focused Tools in the Market Today Leveraging Gen AI?

There are. I would say that the use of Gen AI in logistics tools is still a little new. Tools like Parade, which is a very specific toolset around carrier relationships is leveraging some Gen AI capabilities. Most Gen AI is relatively generic. Tools like Observe.ai or Freshworks are available today with some Gen AI capabilities. 

How Do You Measure Success When Leveraging Generative AI Initially?

We always look at success when we look at automation as reclaimed time. What we mean by that is, are we giving someone a technology that assists to a point where we’re able to redirect them to more strategic activity. The other one is really asking the people who are impacted by it. You need to get feedback so you can understand if it’s being helpful or harmful.

When Should I Start Using Generative AI?

Now! Encourage its use, though with appropriate guardrails and guidelines. It’s going to be a disruptor. Gen AI is not a disruptor quite yet, but it’s getting there, fast. The widespread availability and use will accelerate its impact on many industries and roles. 

What’s an Example of How Trinity Logistics is using Generative AI today?

We’re using it in a couple of different ways. One tool we use is Observe.ai, which is a natural language processing tool. We use it to look at our interactions with customers, look at sentiments, look at certain events, look at what type of interaction was this, and that uses that Gen AI to provide us with that information. Then we have a Development Team, so we’ve started working with some of the code copilot, so assistive coding technology. 

The chemical industry is vital in producing goods and services that touch every aspect of our lives. It’s a competitive market to be in.

Adapting to trends is crucial for chemical manufacturers to stay successful. The most profitable companies will be ones that work with business partners who keep them updated on these trends and embrace any changes that may come their way.

Trends Affecting the Chemical Industry

• Artificial intelligence
• Data analytics
• Specialty chemicals
• Sustainability
• Renewable and bio-based chemicals
• Safety and reducing risk
• Resilient supply chains 

Embracing Artificial Intelligence

The chemical industry has a history of embracing new technologies. Artificial intelligence (AI) is no exception. AI offers many potential benefits for chemical manufacturers. It can help find savings, improve efficiency, and increase productivity. There are so many ways AI can help chemical companies get ahead.

For example, it can help automate manual tasks and analyze vast amounts of data faster. With AI, chemical companies can make more informed decisions and improve quality control. Adopting AI can also help chemical companies improve workplace safety and reduce the risk of human error.

The Growing Significance of Data Analytics

Examining data sets for insights to improve decision-making is becoming more commonplace among chemical companies. Chemical manufacturers can use data analytics in their decision-making to enhance their productivity, reduce costs, and predict critical events that may impact their business. Moreover, they feed AI algorithms this data to forecast better and optimize their operations.

Accessing data can provide insight into the quality control of products or visibility into bottlenecks affecting their chemical supply chain. This data can help them pivot and improve their customer’s experience. Using data analytics is a great opportunity for chemical manufacturers to drive growth and profits.

A Rising Demand for Specialty Chemicals

Many other industries use specialty chemicals, like personal care, electronics, packing, and pharmaceuticals. In fact, the pharmaceutical industry accounts for the largest segment using them as the need for more medication grows.

Additionally, agrochemicals are another significant user of specialty chemicals. The growing population means an increased need for food and food production. Agricultural land is dwindling, and increasing the crop yield per acre of land becomes more important, increasing the demand for specialty chemicals.

Sustainability

The pressure on chemical manufacturers to reduce the environmental impact of their operations and products has never been greater. Regulatory agencies have placed stringent regulations with ambitious emission reduction goals for 2030. While many in the chemical industry have prioritized sustainability in their business, there is still work to do.

Green chemistry is part of this trend that’s gaining momentum. Green chemistry focuses on the processes and products to reduce the effect of hazardous materials and negative environmental impact while conserving natural resources for future generations. Green chemistry embraces recycling technologies, alternative energy resources, and other sustainable practices. This pushes many chemical manufacturers to review their current business strategies.

A Greater Need for Renewable and Bio-based Chemicals

A growing demand for renewable and bio- or plant-based chemicals should be no surprise.

This trend aligns with sustainability goals and brings the chemical industry opportunities for savings and new market opportunities. Companies are exploring avenues like synthetic biology, bioremediation, and the production of bioplastic or biodegradable materials

Prioritizing Safety and Reducing Risk

Safety and mitigating risk are huge concerns for businesses in the chemical industry.

Cybersecurity is a rising trend and threat for many companies. We see it all over the news. Hackers and scammers are becoming more tactical in cyber-attacks and company breaches of private information. It’s crucial for chemical companies to put in place security measures and training to keep their businesses safe.

The transport of hazardous chemicals has also recently gained special attention in the news. Rail transport accounts for around 19 percent of chemical shipments. Recent derailments, like in East Palestine, Ohio, have raised concerns about transportation safety.

Many chemical companies are also investing more in developing safer chemicals and products. Their concerns are not only to be less harmful to the environment but to human health as well.

Improving workplace safety is another concern. Companies install new safety protocols, enhance employee training, and use technology to address this.

Building a Resilient Supply Chain

In the last few years, companies realized how vulnerable their supply chains were.

In a survey by the American Chemical Council, 97 percent reported modifying operations due to supply chain disruptions. Chemical companies are focusing on reducing supply chain risk and increasing flexibility. With 25 percent of the U.S. economy depending on the chemical industry, it’s important their supply chains keep moving.

Keep Your Chemical Supply Chain Ahead of the Trends

Keeping your chemical company ahead of evolving trends and the competition is important. Having business partners that stay tuned to what’s happening in the chemical industry can be invaluable.

Trinity Logistics can help you with many of these trends through our services. Whether you have sustainability goals, are looking to build supply chain resiliency, or need technology to improve visibility and offer data analytics, we have solutions.

We’re members of many industry-related associations like the National Association of Chemical Distributors (NACD) and are Responsible CareⓇ Certified, so you don’t have to worry about falling behind in news or trends that may affect your business. When you work with Trinity Logistics, your designated expert will keep you so informed that you’ll likely know what’s affecting the chemical industry before any of your competitors do.  

That’s just part of Trinity’s People-Centric service you’ll get to experience when working with us. We understand that people are at the heart of all businesses, so that’s who you’ll talk to – a dedicated relationship at Trinity. It’s also who we truly serve – your people.

Our goal is to improve lives, and when you decide to work with Trinity Logistics, you’ll see just that – improved life satisfaction amongst your employees and customers.

The following is an opinion article on AI in supply chains, written by Russ Felker, Chief of Technology (CTO) of Trinity Logistics.

Artificial intelligence (AI) continues to grow its presence in our everyday lives, businesses, and now, supply chains. In a recent MHI Annual Industry Report, 17 percent of respondents said they use AI, with another 45 percent stating they will begin using it in the next five years. And of more than 1,000 supply chain professionals surveyed, 25 percent stated they plan to invest in AI within the next three years. While AI in supply chains has its benefits, it continues to be overhyped as a replacement for human cognitive abilities.

AI in Supply Chains: We Need to Change Our Focus

The technologies leveraged by today’s AI offerings fall flat when applied to the complex day-to-day of supply chain interactions. We need to stop chasing the inflated promises of artificial intelligence and start focusing on the very powerful pattern recognition and pattern-application technologies marketed today as AI to support our teams more effectively. Instead of focusing on AI, we need to reorient on CAI (computer-aided intelligence).

Now, this might seem like a semantic argument, and to a certain extent it is, but the difference between artificial intelligence (AI) and computer-aided intelligence (CAI) is distinct. You might ask, “What does it matter if the technologies are being put in place and create efficiencies?”  “So what if it’s called AI?”  I would say it makes all the difference in the world.

What AI in Supply Chains Currently Does Well

First off, let’s talk about the technologies backing the products that include AI.  As with many technology implementations, they are, by and large, applying rulesets to data. Being able to quickly process a defined pattern against a large data set is both no mean feat and hugely beneficial in a supply-chain setting. In the end, however, these implementations are no different than a rules engine – albeit one with a high degree of complication. For example, take an area of the supply chain that has had this form of technology applied to it, quite successfully, for many years – route optimization.  

Optimizing a single route is relatively simple but optimizing the routes of multiple vehicles in conjunction with related schedules of item delivery commitments and layering in things like round-trip requirements and least amount of non-productive miles (miles driven without a load) and the level of complexity moves well beyond what an individual could do in a reasonable period of time.  What can take on this type of task is a processing engine designed to apply complex patterns within a given boundary set – and that’s what current implementations of AI can do. And they do it well.

Why AI Can’t Replace Humans

The first problem comes in when we examine the stated goal of AI – the ability for a machine to work intelligently. The difference between hype and reality is in how we interpret a keyword – intelligence. Even the most recent and hyped AI systems continue to fail at the same core intelligence functions such as understanding nuanced context and broader application of existing patterns.  

Take Gato from DeepMind, a division of Alphabet, as an example. While it can examine an image and draw basic conclusions, the context and understanding are both entirely missing from its analysis. Tesla provides another example where a driver had to intervene as autopilot couldn’t recognize a worker holding a stop sign as something it should avoid. These limitations minimize the tasks for which AI technologies can, and should, be leveraged.  

The second problem is related to the first. The acceptance of “AI” from teams has been wrought with, at a minimum, intense change management and, in the worst case, rebellion. If you are bringing in AI to a team, why wouldn’t they draw the conclusion that your goal is to replace them? To start down the path of both realistic expectations from senior management and more widespread adoption of technology, we must change the approach we take with stakeholders impacted by implementations of AI. We need to talk about CAI.

It’s Time to Set the Stage for CAI

Just the acronym alone talks to a much more practical and achievable marriage between a person and a computer. It’s not the computer that’s intelligent; it’s the person using the computer. What a computer can be taught to do, is to effectively deliver relevant information to a person at the time they need it based on their job function and recognized point in the process. So instead of using a technology such as a recommendation engine to pick a product you might like or a movie you’re likely to want to watch, let’s turn our focus to delivering salient business information to our people. We can effectively use analytics and machine learning to create data recommendations and deliver those recommendations directly to users in their primary applications at the right time in their process, so they don’t have to go find data in multiple reports or sites. Once a pattern is recognized, by people, and the data is organized correctly, again, by people, we can use things like machine learning and analytics to deliver that result set effectively and consistently.  

What this approach achieves is reduced interaction by a person and the machine reclaiming time for people to connect with customers outside of transactional conversations. By providing relevant data in-process, you make your team more efficient in their use of the system and create more opportunities for person-to-person interactions and relationships. The goal of any system implementation should be to reduce the time needed for a person to interact with it to achieve the desired result. This is different from having the perspective of the machine doing what a person does – which can be a misguided goal of AI. Instead, the system needs to be built to strategically leverage AI in areas that support the reduction of repetitive, rote work, enabling teams to focus on higher-value work.

A 3PL Focused on People

As a 3PL, a large part of our work tends to gravitate toward the identification and management of exceptions, but many times that is reactionary. We can leverage the technologies present today to enhance exception identification and management. Via AI-enabled supply-chain systems, information can be more present for teams to apply their intelligence, experience, and skill to solving issues optimally. The ability to recognize early in the life of a load the potential of a delayed delivery enables teams to make proactive adjustments with the receiving facility and the recipient. We can gather documents automatically and provide the information in a consumable fashion reducing the amount of manual effort to extract relevance from the documents.

As a 3PL we rely on two primary skills – intelligent use of data and building and maintaining relationships. Neither a computer nor an algorithm can do either of those alone, but a person backed by a Computer-Aided Intelligence system can. Creating systems that focus on CAI is what allows Trinity’s true source of intelligence, our team, to shine and deliver consistently phenomenal results for our customer partners. Now, you might be the exception and prefer to converse with a chatbot, but I’m guessing if you read this far, you’d rather talk to a person – which is what you get when you call Trinity – a person, backed by computer-aided intelligence systems, who is ready to do the work to create a relationship with you and deliver phenomenal results.

Staying up-to-speed in leading technology requires time and investments. With all the current and upcoming logistics technology, it can be confusing for shippers to identify what will have the best impact to stay competitive now and in the future. 

HOW LOGISTICS TECHNOLOGY CAN HELP

Businesses today have never been in so much need of change and upgrade with their technology. Their list of challenges to overcome is never-ending. They have retailers demanding more visibility. Then there’s the struggle of finding capacity, managing costs, meeting service requirements, creating a more resilient operation, and more.

There are several current and emerging technologies available to help to address many supply chain problems. There’s a lot to go through, so let’s dive in and see how logistics technology can help.

…WITH CAPACITY

The ability to match a carriers’ network to a shippers’ network is very important. At the end of the day, you still need to match a driver and truck with an available shipment. Available logistics technology can help make that happen, but there still needs to be more adoption of it for it to be more effective.

…..WITH RISK MANAGEMENT

One thing the pandemic taught us is the importance of risk management and resilience. Mitigating your risk comes down to using technology to make better decisions faster by using better data. You must use a network of data to measure yourself against the current market and your peers.

…WITH PRODUCTIVITY AND COST MANAGEMENT

Shippers have an ongoing need to improve productivity and cost management. Technology can help you create win-win opportunities to match loads to available capacity. Or get more committed capacity and good on-time service at a reasonable cost. Logistics technology can help you be more productive while better managing your costs.

…WITH CARRIER SELECTION

Carrier selection can be time-intensive. The process of calculating the best combination of rates and lanes for a particular shipment can be lengthy. Logistics technology automates the carrier selection process, reducing your time spent. It allows you to select the best carrier for every shipment in real-time based on the cost and service level. Technology also helps with carrier vetting through digital applications and API feeds. 

…WITH SHIPPING UPDATES IN REAL-TIME

Most customers and shippers now expect real-time tracking. Technology allows shipment data like tracking and more to your customer in real-time using methods like APIs or geofencing. The days of frustrating phone calls to chase down freight locations are now history.

…WITH IMPROVED ROUTING

Load planning and driver routing can impact your logistics costs. Companies that have complicated delivery patterns can’t really be sure their network is optimized no matter how much time and money they use to plan without technology. Technology can do in seconds what it would take a human hours to do and do it accurately every time. This comes as a major benefit when developing routes incorporates several factors, like rates, delivery windows, and more.

…WITH REDUCED PAPERWORK

Logistics has always handled a lot of paperwork and data. For shippers, it can be easy to become bogged down in all the manual processes that they are responsible for. Not to mention, a single error can cause problems up and down the supply chain. Technology allows you to cut down on errors and time, freeing you to concentrate on more productive tasks. It also allows for easier storage, giving quick access to anyone who needs it.

….WITH GREATER TRANSPARENCY

Thanks to technology, the supply chain is more transparent than ever. Your customer’s expectations and needs have increased to include transparency. Logistics technology enables your customers to receive instant answers to their queries and delivery status. This feature has gone from a nice extra into a necessity for you to stay competitive.

…WITH EFFICIENCY AND FASTER PROCESSES

Technology has led the way to supply chains becoming faster and more efficient. Through warehouse and transportation management systems, businesses can quickly pull data, track resources, and reduced stock with real-time reporting. Through full visibility across your supply chain, potential errors, risks, and opportunities are seen, allowing your business greater efficiency.

…WITH COMMUNICATION

Good communication creates improved business. Technology has made this possible by changing the supply chain for the better. The software enables teams to input data that is accessible for all stakeholders. Technology also allows better insight data, allowing your company to better forecast and communicate your requirements. An increase in your communication also allows for a stronger relationship between you and your stakeholders. 

…WITH HAPPIER CUSTOMERS

The ultimate consequence of the benefits outlined above is happier customers. More efficient logistics operations mean that your freight gets out of the warehouse and to your customer faster. Through centralized storage plus real-time tracking removes any uncertainty for your customers. Technology increases transparency and communication between all stakeholders. 

TECHNOLOGY TRENDS TO WATCH

The logistics industry has perhaps the most to gain from new technologies. In recent years, we’ve seen a massive advancement in areas like artificial and augmented intelligence, advanced analytics, and automation. These advancements also bring new expectations, forcing companies to adapt or fall behind. There’s also more pressure coming from customers demanding their products come faster and cheaper than before. 

Here are the top logistics technology trends your company should be keeping an eye on and consider implementing.

ARTIFICIAL AND AUGMENTED INTELLIGENCE

The logistics industry has started using artificial intelligence in their transportation and more. AI has been making a huge difference in logistics through applications like warehouse automation and predictive optimization. According to research, using AI in logistics can increase companies’ gain by more than 50 percent a year. 

There’s also augmented intelligence. Augmented intelligence combines human intelligence with AI automated processes. According to Gartner, augmented intelligence is its way to create $2.9 trillion of business value. This would lead to an increase of $6.2 billion hours of worker productivity globally by the end of this year. Augmented intelligence is expected to be used more to allow businesses to do their jobs quicker while reducing mistakes and allowing for cost savings. 

DIGITAL TWINS

Digital twins may be one of the most exciting logistics technology trends to keep an eye on. As many know, products are never the same as their models. Modeling currently doesn’t consider how parts wear out and need replacing, how fatigue accumulates, or how owners make changes to suit their needs. Digital Twins technology changes this once and for all. 

Digital Twins allows you to engage with the digital model of a physical object like we would with their physical counterparts. The potential uses for this in logistics are vast. Digital Twins could collect product and packaging data to identify potential weaknesses and recurring trends to improve future operations in shipments. Warehouses could use it to create accurate 3D models of their centers, experimenting with the layout or the introduction of new equipment to the impact with no risk. Logistics hubs can create Digital Twins and use those to test out different scenarios to increase efficiency. 

REAL-TIME SUPPLY CHAIN VISIBILITY

Supply chain visibility is no longer an extra benefit for companies to have. It’s now needed and is taking another step forward – becoming real-time. 

Real-time data is more in demand by customers and carriers than ever. New startups are creating technology that promotes a quick response to change by allowing companies to use real-time data. This data can include things like traffic patterns, weather, or road and port conditions. Companies that make use of an integrated supply chain are reporting to be 20 percent more efficient than those without.

IOT SENSOR TECHNOLOGY

You can’t mention visibility without bringing up the Internet of Things (IoT) Sensor technology. By using connected IoT devices on parcels, it allows warehouses to track inventory or shipped freight. Container management that’s powered by IoT can be made easier with real-time monitoring. You’ll see increased fuel efficiency, preventative maintenance, and container operations more proactive versus reactive.

BLOCKCHAIN

Blockchain is an open ledger of transactions distributed among computers in each network. Since everyone has access to the shared blockchain, there is complete transparency. This also makes it impossible for users to hack into. It also makes it easier for different carriers or shippers to share data. Before a company can completely adopt blockchain, there are a few steps required. First, companies need to digitize, standardize, and cleanse their data. Then companies must form an ecosystem of partners to operate in a shared, permissionless blockchain environment.

Blockchain has grown to be a big buzzword as one of the most overhyped logistics technology trends. That’s because it depends on its market development and on the partners using it. Blockchain’s concept has also been difficult for the public to grasp. Despite its strong potential both in and outside of logistics, there’s been a lack of real development. 

Yet, there are some pilot projects and small-scale operations in effect to keep watch of. UPS and Warren Buffet’s BNSF Railway recently joined the Blockchain in Transport Alliance. 

DATA STANDARDS AND ADVANCED ANALYTICS

Data in logistics has always been isolated. Companies store their data in whatever way they deem fit. This leads to a fragmented system, allowing inefficiency, and making it difficult to digitize operations. 

One of the biggest logistics technology trends points out that isolated data will not be an option if you want to keep up with changing times. The Digital Container Shipping Association (DCSA), created in 2019 recently set new data standards in container shipping. Their mission is to create common information technology standards for digitalization and interoperability to make the shipping sector more efficient for both customers and shipping lines. 

Other logistics fields still have work to do to solve data inconsistencies. There are many young startups focused on creating predictive and advanced analytics platforms as a solution. When data becomes standardized and digitized across the industry, all companies will benefit. Logistics data is essential for planning future deliveries and understanding what goods the market needs. 

GROWING NEWCOMERS

New technology isn’t the only one shaping the future of logistics. There are also new business models and industry players. Without a need for a rich asset background, these startups tend to focus on the asset-light parts of the supply chain. Since they have more flexibility, they can offer quicker pricing and quotes. 

An example of this is Uber which launched Uber Freight in the U.S. in 2017, now expanding into Europe and Canada. There’s also Amazon expanding its expertise in warehousing and transportation. They’ve already made plenty of headway with Prime Air, the electric drone service it’s building, to fly up to 15 miles and deliver packages under five pounds, to customers in less than 30 minutes. It’s also recently reported that the company has been importing new Amazon-branded intermodal containers. 

SUSTAINABILITY POWERED BY TECHNOLOGY

Sustainability is a trend across all industries. More people are choosing companies that have an eco-friendly reputation. Companies are investing more in reducing emissions. As a result, ecological technology is beginning to influence logistics. For example, last-mile delivery is very time and energy-consuming. It presents many opportunities for a fresh approach. To lessen its environmental impact, companies leverage technologies like electric vehicles or AI-based software to calculate a route with low emissions.

AUTONOMOUS VEHICLES

Autonomous vehicles are still in the early stages. Even so, it’s a huge, discussed technology. A few short years ago, they were more unreal, but many companies are investing in them. Self-driving trucks could be efficient in operating busy roads to predict and analyze traffic. They could also help ease some of the driver shortage and capacity.

WAREHOUSE ROBOTICS

Warehouse operations have undergone a significant shift recently.

Technology has been progressively integrated and the trend looks to continue. According to the Global Customer Report of 2019, there has been an 18 percent YOY increase in the testing of warehouse robotics. Robotic technology comes in various forms, like wearable technology, driverless vehicles, or multifunctional robots. No matter the form, it can improve the efficiency and speed of warehouse processes. Industry trends focus on the automatization of manual work. The goal is to make routine work cheaper and more comfortable for their business. It’s also used to improve monitoring, receiving, and dispatching products in the warehouse.

CURRENT TECHNOLOGIES YOU SHOULD LOOK INTO

TRANSPORTATION MANAGEMENT SYSTEMS (TMS)

A cloud-based TMS provides you with real-time visibility of your transportation, data insights, dashboards, reporting, and analytics. TMS technology may not be new, but its technology that continues to improve and offer a lot of insight into your logistics. Through real-time data insights, TMS technology can help you reduce risks and spot opportunities for cost savings through efficiencies. In an ARC survey, respondents indicated freight savings of 8 percent through the adoption of a TMS.

ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

Artificial Intelligence (AI) and Machine Learning (ML) support inventory, demand forecasting, scheduling, and predictive analytics. Tasks that could take people days or weeks are reduced to minutes. Through automation, you can save time and increase efficiencies in your supply chain. The level of automation can be semi-automated, completely automated, or a mix of both. 

SHIPMENT TRACKING SYSTEMS

Years ago, customers would book shipments, receive an estimated delivery date, and then be left waiting. Now software allows customers to access tracking on their shipment 24/7. User experience is enhanced, and time and money are saved. Here at Trinity, we currently use FourKites, MacroPoint, and Trucker Tools for our shipment tracking. 

INTERET OF THINGS (IoT) AND RADIO FREQUENCY IDENTIFICATION (RFID)

Many devices made have built-in WIFI capabilities or sensors. The easy access to WIFI and the internet connects everyone to everything, which is why it’s called the Internet of Things. The adoption of IoT is on the rise. It opens many opportunities in the supply chain, like reducing costs and delays. Sensors can be placed into trucks, cargo ships, trains, on parcels, or more. They can also connect to an alarm system or have a dispatcher that monitors and tracks. One example would be temperature monitoring for temperature-controlled products. IoT isn’t new technology, but it continues to impact and grow in logistics. 

RFID technology is a popular way a company can track inventory. A tag or sensor gets placed on a product, and radio waves are sent out. Data then gets received and processed by the company. RFID tags are like barcodes, but the superior speed of delivered information and data processing is more appealing. 

AUTONOMOUS TRUCKS AND DRONES

Autonomous cars are already a reality with trucks not too far behind. Companies like Embark and Uber have already used autonomous trucks, and Tesla will be releasing their electric truck soon. Even though the trucks are not completely driverless yet, it’s a huge step in this breakthrough technology. As mentioned prior, Amazon will be using electric drones soon through Amazon Prime Air. The drone deliveries are still a few years out, but the idea of an even quicker delivery is appealing.

FIND TECHNOLOGY THAT WORKS FOR YOU

With so much available and upcoming in logistics technology, shippers should partner with experts who can offer customized solutions. Be sure their technology is not only flexible but that they stay on top of technology trends. Adopting technology in your business can provide you with more visibility, connectivity, advanced analytics, and more. Technology can help you enable better collaboration with your stakeholders and offer greater efficiency across your entire supply chain. 

Here at Trinity, we understand technology can make or break your supply chain. This is why we continue to stay ahead of cutting-edge tech and make sure to have the best technology applications available to you. Additionally, by working with Trinity, you’ll not only have the data and applications you need but the experienced tech and logistics professionals ready to serve you.

To find out more about what best-in-class technology applications you gain with Trinity, 

To learn more about Trinity’s TMS and Managed Services through a free supply chain analysis, request a consultation. 

Author: Christine Morris