Are you tired of having supply chain disruptions getting in your way and increasing your operational costs? Well, don’t be. We got your back.
All supply chains have risks, and they will only continue to get bigger. With everything getting worse, from tariff disputes, geopolitical instability to extreme weather events and cyberattacks, your supply chain is under siege.
Let’s face it:
While supply chain disruptions have never been higher, many organizations are still tackling these problems with siloed tracking methods, Excel sheets, and… manual workarounds. That’s a no-go. Manual efforts are a big deal in risk management: the bigger the supply chain disruption, the more manual work is required.
It is frustrating that despite the urgent need to identify and address risks earlier, an estimated 75% of logistics organizations do not have risk visibility in real time. In addition, current supply chains are in the midst of various trade disputes, geopolitical tensions, and financial uncertainties that have never been more challenging.
But with the latest technology advancements, things are changing. Thankfully, there are a ton of technological tools that can help businesses monitor, identify, and address potential supply chain risks early. In this post, we break down the leading solutions and help you pick the right ones for your needs.
In this guide, you’ll find:
- Why Technology Is Important for Logistics Risk Management
- 4 Top Technologies for Logistics Risk Management
- 8 Tips for Building a Smarter Logistics Risk Strategy
- 6 Common Pitfalls to Avoid
Why Technology Is Important for Logistics Risk Management
Before we go to the solutions, let’s start with the basics. After all, how can you pick the right technological tools if you don’t know what you need them for?
Logistics risk management is the process of pinpointing, identifying, and overcoming the forces and events that are likely to harm an organization’s supply chain operations and even its global supply chain presence. Logistics is, of course, full of risks and dangers that include trade disputes, extreme weather, earthquakes, and fires, and even disease outbreaks. In this case, safety, risk management, and good planning must be at the top of every company’s agenda.
To get started, here are three main points of what makes a risk management plan and why it is needed:
- Identify threats and hazards that may negatively impact logistics and transportation operations. For example, your company may identify the main suppliers that account for an outsized share of your input supply and have the greatest potential to face trade disputes.
- Once potential threats and hazards are identified, the next step is to examine the potential consequences of each risk. In the logistics and transportation industry, understanding and evaluating the consequences of a risk might include evaluating how delays caused by a threat or hazard could harm customer service, revenue, and customer satisfaction.
- After potential risks have been identified and consequences have been evaluated, you must make an informed decision on the best course of action to address each risk. Mitigating each risk can consist of managing each risk proactively before the risk occurs.
Now, it’s evident why you need technologies in the mix. While risk management includes planning, your team can greatly benefit from the risk detection visibility in real-time with the latest tech tools. The only way to stay on top of every situation in the modern digital world is to implement state-of-the-art AI, IoT, and cloud-based platforms to your operations. If your company has had the chance to streamline its operations with technological solutions, then, of course, great. If not, you’re in the right place.
4 Top Technologies for Logistics Risk Management
What are the best technologies for your company to manage and streamline its operations? Let’s go through the main leading technological solutions.
AI and Predictive Analytics
Artificial intelligence and predictive data analytics are possibly the two most valuable technologies for supply chain operations in the 21st century. AI systems use machine learning algorithms to analyse and process big data in logistics to identify patterns and trends and make predictions. Data scientists and AI analysts train algorithms with a historic set of data, called supervised learning, so the system can then recognise those patterns in new data.
AI technologies in logistics work best with data from different sources to find patterns. The latest risk detection systems use a combination of information sources such as:
- Social media, news reports, and online discussions to identify leading indicators of potential supply chain disruptions
- Weather forecasts to predict natural disasters
- Political and economic analyses to identify geopolitical risks
- Publicly available financial statements and other financial information sources to detect supply-side financial instability
- Internal production and distribution databases to identify network anomalies
AI can save lives by sending out early warnings of natural disasters based on weather patterns or even anticipatory alerts on potential industrial accidents before they happen based on process analytics.
With data from multiple sources, AI-powered tools provide decision-makers with a risk management dashboard that offers a more comprehensive view of leading indicators of supply chain disruptions. Despite this potential, only 10% of logistics companies have fully adopted generative AI according to BCG research.
IoT and Real-time Tracking
Internet of Things technology allows real-time tracking of goods throughout the logistics supply chain and shipments and monitoring. Sensors collect data about the condition and location of goods and send this information to the cloud, where it can be viewed by relevant people with access to the system.
IoT in risk management works with tools and systems that use tags and sensors that send information about the condition of goods and their exact location at all times, enabling real-time tracking and monitoring of goods. Tags that incorporate sensors can provide more precise information about the condition of items.
IoT can also be used to implement early warning systems in places prone to natural disasters. Sensors can detect the first signs of an earthquake or flood and send alerts to the appropriate authorities and personnel before the natural disaster occurs.
Cloud-Based Platforms
Cloud computing platforms can store massive amounts of data and information about a company’s supply chain, making it easy to access information from anywhere in the world. The latest systems utilise scalable cloud computing capabilities to store big data from different data sets for historical analysis and predictive risk analytics.
Cloud-based systems that can use real-time data from multiple sources are a godsend for disaster prevention. For instance, if data on leading risk indicators and past disasters are uploaded to the cloud, emergency and rescue services can easily access and analyse this information to provide early warnings of impending disasters.
Automation and Robotics
Automation systems use technology to reduce or eliminate the need for human intervention in logistics and transportation processes. Robots are used in warehouse operations and loading and unloading operations. Route optimisation software is also used to improve the efficiency of transportation processes.
In addition to streamlining operations and increasing efficiency, automation systems and robotics can also play a key role in ensuring the safety of workers and staff. Robots can be used to perform dangerous tasks that may be hazardous to people, such as lifting heavy objects or handling dangerous goods.
Robots can also be used to improve risk management by performing tasks that are considered dangerous to humans, such as handling toxic or radioactive materials, working in extreme temperatures, or working in high-risk areas prone to natural disasters.
Automatic work systems such as drones can also be used to deliver emergency aid to people in disaster areas and monitor situations in areas at risk.
Wrapping It All Up
AI and IoT technologies have revolutionised supply chain operations and enabled early warning of potential risks and have become an integral part of every logistics company.
AI-powered risk detection systems and IoT sensors and trackers are effective and practical solutions. When they are combined, companies can get an even more comprehensive and in-depth view of the main risk indicators and leading risks in the supply chain. IoT sensor systems can collect data on potential risks and upload them to the cloud for further processing with the help of AI tools.
