Solving digital freight matching’s phantom data problems

‘Post and pray’ based on bad info is harming digital freight matching prospects. But how can phantom data issues be fixed in supply chains?
8 February 2023

Phantom menace: ghost loads on load boards arising from poor data management are a headache for transport operators. Image credit: Shutterstock Generate.

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Mention phantom inventory to e-commerce operators, and their faces will likely turn a ghostly color. Put simply, phantom inventory is a pain for retailers as the end result is typically lost sales. Phantom inventory refers to stock that’s showing up as being available on the shelf or in the warehouse. But, frustratingly for webstores and their online shoppers, digital stock records don’t tally with physical items. Reasons for the mismatch could include fraud, theft, human errors in recording goods in, and poor inventory counts – to give just a few reasons for e-commerce sites having ghost-like products listed on their systems. But the phantom data problems don’t stop there. Digital freight matching services used to move products along the supply chain can also be prone to bad information.

Putting yourself in the shoes of a component supplier with device maker customers anxious to assemble products for a backlog of orders – you start to see how phantom data problems in transportation come about. “Shippers who have goods that have committed to getting them to their customers have to find somebody to perform the service of getting the goods from their dock to the customer’s dock,” explains Michael Darden – Founder and CEO of DFM Data – during an interview with Joe Lynch, host of the Logistics of Logistics podcast. “And when they do that, their shopping is done in a lot of different ways – phone calls to brokers, phone calls to past carriers, phone calls, emails to everybody that they know – and before you know it, that one load that they have to move to their one customer is on 20 different load boards looking like the same load.”

Fixing the problem of ghost loads on load boards

In the transportation sector, phantom data problems arise when multiple sources of truth are created by different providers. And ghost load issues occur every time a shipper snaps up a job on the board that’s already been taken, but hasn’t been removed from the list. Human reconciliation workflows running ad-hoc behind the scenes are never going to be able to stay ahead of digital systems, even during quiet periods, let alone when things get busy. And the industry is screaming for a better solution.

One option that’s gaining traction for fixing phantom data problems in digital freight matching is the use of blockchains. What’s more, digital ledgers don’t just provide a single source of truth – to avoid any double-booking confusion – they offer transparency too. Also, because everyone can have a copy of the information, there’s redundancy built into the process, making supply chain information systems less prone to a single point of failure. Blockchains paint an appealing picture, but how exactly do they work?

If you try and find the answer to how blockchains work using a search engine, you’ll be served up terms such as hash functions, nonces, and public-key cryptography. But to put your understanding on a firmer foundation, it’s worth digging a bit deeper and considering how a digital ledger works at a fundamental level. Starting with a paper ledger, we can imagine a list of entries, which could be transport costs between each node in a supply chain. And it’s straightforward to imagine converting this list into a spreadsheet, for example, which could be shared between stakeholders. But if anyone can edit the entries, how can the integrity of the data be preserved? And how do you know, which version of the spreadsheet is the most up-to-date?

Each entry (or block) in the ledger can be stitched together using one-way operations known as hash functions. The hash value provides a running integrity check of all the entries that precede it in the chain. If anyone goes back and modifies the historical data, the current hash value will change, indicating that a change has been made. Also, rather than just including the raw node-to-node transport data, each of the blocks can be signed, or encoded, using a private key. Stakeholders can then determine exactly who is responsible for each of the entries by referring to a list of public keys, which are individually paired with private keys – and act as a lookup table to see who’s signed what.

Having a tamper-proof digital ledger brings other benefits too. For example, the traceability of goods becomes much easier for stakeholders to demonstrate. Supply chains can have many individual steps – goods can be repackaged, aggregated, and distributed at various stages. And, to avoid issues such as counterfeiting – which can occur when security gaps exist – all activity can be tracked on the blockchain. Digital ledgers won’t stop bad actors from physically tampering with goods, but any interference will immediately show up as an error in the blockchain’s hash values (the digital seals between entries). What’s more, the point at which the numbers cease to add up readily highlights where supply chain tampering is occurring in the shipping process. And this information can be used to bolster the integrity of operations on the ground.

The fact that large shipping companies, which – like their vessels – are slow and steady rather than fast and reckless, are taking a serious look at blockchain technology to streamline supply chain operations, highlights the bright prospects for digital ledgers in transportation. And many in the digital freight matching sector will breathe a sigh of relief if blockchain systems can bring an end to phantom data problems and ghost issues on freight load boards.