Author: Avantika Sharma
Contact: LinkedIn
For years all this has been done on paper, by telephone and a fair bit of “go on faith”. A batch went down a manufacturing line and all that went downstream hoped that it would come on time and intact. It’s a quiet time of change that’s ending. A digital thread is the continuous data rich record which connects sensors, connected devices and machine learning models together to track a product from raw material to the final delivery, which is what people now refer to as a digital thread. It’s not only impacting the way companies track goods, but also their approach to trust, risk and accountability throughout their entire network.
What the Digital Thread Actually Means
The essence of the digital thread is that it’s a continuous, real-time stream of information. A sensor identifies each time the product changes hands, location, and/or temperature and inputs that data into a common system. Rather than static records being updated on receipt of the shipment, a rolling view is now provided, updated almost in real time. The difference between traditional tracking and traceability is that traditional tracking would be recorded as occasional snapshots, while traceability would be done in a continuous manner.
The Role of IoT: Eyes and Ears Across the Network
Sensorial layer of the system – internet of things devices. GPS trackers periodically give their geolocation. Vaccines or fresh produce are shipped in sensitive conditions which are monitored by temperature and humidity sensors. The tags are not only placed on a pallet’s spreadsheet but actually placed on the RFID tag to confirm that a pallet has left a warehouse. These devices individually look like small devices. These two make a reliable and regular supply of ground truth data, which we couldn’t previously collect on a large scale.
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Let’s imagine that there’s a shipment of seafood coming from a fishing port to a restaurant chain. When refrigeration drops too low, a temperature sensor in the container will signal the time, hours before the product arrives at the warehouse. In the old system that was the only time it could be detected when someone opened the box and smelt it. When IoT comes into the world, problems emerge and there’s still time to do something about it.
Where AI Enters the Picture
If nothing can make sense out of raw sensor data, it’s nothing but noise. That’s where AI makes an impact on the supply chain. The machine learning models filter out all of the location pings, temperatures and delivery timings and look for patterns which a human analyst wouldn’t. A model based on historical shipping information can forecast the tendency for a route to experience delays in shipment under certain weather conditions, or for a given supplier to ship products near their quality limits.
Anomaly detection is also increasingly being made an effective use of AI. The system can automatically identify a shipment that suddenly changes course from what’s expected or a batch of components with readings that are out of line with the recorded history of that batch of components. This has a huge impact on sectors such as pharmaceuticals and electronics where the production of counterfeit goods and undisclosed substitutions are still an issue. As opposed to relying on periodic audits, companies are now able to continuously check the authenticity.
Supply Chain Management Market
I recently stumbled upon a report from Roots Analysis which added some quantifiable data to the rate at which this space is evolving. Their estimates place the size of the supply chain management market at approximately USD 31.27 billion in 2024, and it’s projected to reach approximately USD 94.71 billion by 2035. This translates to a compound annual growth rate of approximately 10.60 percent during the forecast period, a relatively high growth rate for an industry that was previously perceived as fairly slow moving. This is a nice reminder that this may be a niche move towards the smarter, more connected supply chain that’s on the rise at the moment, but it’s only the beginning of a long wave.
Traceability as a Business Advantage, Not Just Compliance
All this could be interpreted as being a reaction to the regulations, but it is certainly true that regulation on food safety, conflict minerals and handling of pharmaceuticals has driven them to better tracking. However, because of traceability, it is able to become a competitive advantage on its own. When it comes to coffee beans, people nowadays want to know where they are from, and if their sneakers were manufactured under fair labor practices. For brands that can provide verified data in response to these questions, as opposed to marketing claims, it’s a type of trust that’s difficult to fake.
There is a less talking, more money-making benefit here, too. A defect that can be identified and traced back to the exact factory line that produced the defect or to the raw material batch the defect was made from, will cost the company very little to recall. A business does not necessarily have to deal with a whole product line; it could just have to deal with a small portion of it. That accuracy can be the key to saving millions in times of emergency.
The Challenges Nobody Talks About Enough
All this is not easily done. The number of suppliers, with varying systems and technical maturity is quite large, which is quite a difficult coordination problem. A small provider in a developing area may not be able to provide the services of real time reporting from sensors, thus introducing a gap in the thread. Data quality is another silent warfare. If companies are careless about validation, a poorly calibrated sensor or a network failure (which might cause a few hours of readings to be lost) can jeopardise the confidence that can be placed in the entire system.
There are also questions of ownership of this information and access to it which have a certain legitimacy. Suppliers might not be willing to give buyers sufficient detail of its operations that the buyers will be able to use against it in the future. Implementing the digital thread is as much about gaining trust between business partners as it is a technological issue.
Looking Ahead
It’s quite easy to see the direction of travel. The digital thread will permeate deeper into lower value goods and smaller suppliers, which were too expensive to keep an eye on and too hard to track with sensors, as the costs of sensors continue to drop and the quality of AI models to improve. Originally pioneered by high-risk sectors such as pharmaceuticals and aerospace, it’s slowly moving its way into a wide variety of retail, agriculture and manufacturing sectors.
Not only are the companies who adopt early side-stepping compliance headaches, but they are also avoiding the risks of non-compliance. This is a simple, but increasingly important question that they are developing a supply chain to answer: How do you know this came from somewhere?
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