The market for Digital Twins is estimated to grow from $3.8 billion in 2019 to $35.8 in 2025 as per a recent report. But are you fully acquainted with the concept of Digital Twin and how to leverage it in your supply chain system?
A digital twin is essentially a virtual version of a physical object or system. By replicating a physical entity in its virtual form, you can gather real-time data that can be used to enable better decision making.
What Does a Supply Chain Digital Twin Look Like?
The digital twin can change the way supply chain management works. It gives you the feeling of being there with your shipment even when you cannot physically be there, allowing you to make business decisions based on live facts and predictive insights rather than resorting to reactive (and slower) measures to contain supply chain disruption.
With connectivity at every point in the supply chain, there’s an overwhelming amount of data that must be leveraged the right way. In a world where everything from finished products to RSAs can be tracked in real-time, the standards of one's ability to manage supply chains have risen to the next level.
The supply chain is already always connected, and it produces tons of data.
What matters more is how you use that data and make the most of it.
The digital twin allows you to create a continuous, fine-tuned live network between your physical and digital assets. It creates a virtual replica of the physical and applies statistical analysis and modeling suites that can integrate with and enhance the functionality of disparate systems like:
- Transport Management Solution (TMS)
- Warehouse Management System (WMS)
- Fleet & Asset Management
- Billing & Financial Control System
- Supply Chain Control Tower
A well-laid system gives you the ability to continuously interact with carriers, shippers, and infrastructure support providers for the execution of your Freight Management services, which has far-reaching implications for everyone in the supply chain ecosystem.
For Companies — it allows better analysis (both historic and predictive) to inform better decisions, helps you handle process modeling better for on-the-fly optimization, and gives you an edge when it comes to making split-second decisions that can make or break error-free operational efficiency.
For 3PLs — it allows a more error-free execution and facilitates higher fulfillment rates, which improves customer satisfaction and enhanced OTIF performance. A well-executed supply chain management system also allows you to provide end-to-end visibility to your customers, helping you improve order management, reduce the total cost of operations, and improve customer experience.
For Freight Forwarders — it improves margins as well as your ability to serve customers by autonomously optimizing the process of booking available space on cargo airlines and ocean carriers to ship at the lowest cost possible. The system liaises with external systems to give you better end-to-end visibility, allowing you to provide the same kind of visibility to your customers improving customer satisfaction. It helps you optimize operations, revenue, and margins, and lets you achieve operational flexibility, which works toward reducing your TCO (Total Cost of Operations).
If implemented and operated well, a supply chain management system that’s informed and augmented by a Digital Twin modeling system can, and most certainly will, revolutionize the way operations are planned and managed in a more connected world.
Here’s How You Can Build a Sensor-Driven Supply Chain Digital Twin
Achieving this kind of perfection would make sure that your digital twin mirrors the real world and makes it as close as it would be if you could physically be present there. For your digital twin to be in perfect sync with your supply chain process, it needs Real, Real-time, and Relevant Data.
Real Data — Data is now everywhere and getting data isn’t the greatest concern anymore. In such a scenario, getting crowdsourced data like airline schedules, probable ocean cargo vessel locations, or near real-time GPS truck data will not work. The emphasis right now is not on finding data, but rather, on getting accurate and reliable data that you can bet on.
Real-time Data — Getting real-time data is completely dependent on connectivity, especially when you’re tracking international movement. Any devices that go with your cargo must have reliable roaming capabilities as well as backup connectivity options. Companies that rely on a single mode of connectivity — whether it’s GSM or LPWAN — run the risk of losing connectivity if the networks their sensors are streaming on fail. You need to ensure that the device you use can piggyback onto whatever options are available locally, and can switch between them intelligently enough to maximize connectivity and battery life.
Relevant Data — Ask yourself the question — what do you want to know about your physical asset or shipment, and how is that data useful for you? — the data you draw on should be direct and relevant to your requirements.
Can Your Digital Twin Act on Your Behalf?
AI + RPA + Human Rationale
Because in the end, it’s not just about deciding what to do, it’s also about doing it.
Once you have real, real-time, relevant data in place, you can work on the:
Artificial Intelligence (AI) — that can infallibly predict supply chain events so that your business decisions are timely and relevant, followed by
Robotic Process Automation (RPA) — to bring in automation, so no action gets delayed or haywire, one that can drive onward systems like changing a window of delivery.
You should be able to guide your physical assets remotely using a combination of AI + RPA — ensure that the digital twin helps inform both decisions AND corrective action — just as you would if you were in the picture.
But can RPA Compensate for Human Intervention?
Human Rationale — Think of a situation wherein you need to coordinate with staff in the field where, for instance, a cold chain shipment’s temperature is rising while it’s waiting in a holding area for loading or unloading. While RPA works to flag such situations, it still needs human intervention to effect change. Alerts need to go out to the right personnel at the right time so they can take corrective action. An AI-driven monitoring system can stay on top of things when it's business as usual, and especially when things go awry, but in the end, it’ll still rely on human intervention to resolve situations as they happen. Well, at least until we’ve got real-world robots to step in and take charge.
To make the most of an intelligent system that combines the best features from live monitoring, predictive insights, and instantaneous corrective action, you need a mix of AI + RPA + Human rationale.
In short, here's what you must do in order to set up the supply chain digital twin:
- Recreate your physical asset, process, or system.
- Get your sensor game right.
- Ensure that your physical object can communicate seamlessly.
- Make sure you’re plugging in real-time data from the physical version of your asset to the virtual model.
- Implement what you can to automate process management and exception handling using AI + RPA.
- Plug the gaps that automation can’t with Human intelligence.
Using a sensor-driven supply chain digital twin, you can basically run your entire supply chain virtually, remotely, and with minimal overheads in terms of man hours and management costs. All you need is to make sure that along with your Digital Twin, you also implement elements like AI, RPA, and human capital to make the most of your system.