Since the pandemic, the global supply chain has come under incredible pressure and scrutiny, taking a rare place on center stage. The challenges of managing an efficient supply chain and remaining profitable in the face of such disruption have never been more significant.
Alan Pelz-Sharpe
Researcher, Impact of AI & Blockchain in the Enterprise
Unsurprisingly, there has been an important pivot in looking toward supply chain technology to resolve many of these challenges, whether they be moves to:
Supply chain technology can help bring about much-needed change, but there are no silver bullets.
Even with advances in supply chain management and experiments with Internet of Things (IoT) devices, much remains undone and unresolved, as good technology depends on good data. Without good data, the technology can do very little.
And though we have enormous amounts of data flowing through the chains, too much of it is unreliable or inaccurate. For supply chain executives, the lure of technology is strong, and you should embrace it.
Still, you’ll need to work hard and face harsh realities if you are to leverage emerging technologies in supply chain management successfully.
The first reality is that all technology assumes that your data is accurate; in fact, technology has no way of knowing if the information has been misfiled or keyed incorrectly. For example, complex bills of lading (BOLs) or manifests often contain multiple minor errors (dates, quantities, freight class, etc.). These errors can be compounded further by inaccurate manual key entry work.
Such errors cause numerous disputes, delayed payment cycles, and even returns.
Similarly, multiple copies of the same document in the hands of various third parties across the chain can introduce further errors and bottlenecks. If not identified immediately, these simple errors and problems become significant issues resulting in acrimony, inaccurate forecasts, late deliveries and unpaid bills.
Hence, it would be best to consider investing first in automating standard document processes to reduce manual key entry work and improve its accuracy. Supply chain technologies such as robotic process automation (RPA), intelligent capture and automated data extraction can deliver a fast return on your investment for this challenge by immediately enhancing process efficiencies and providing you with the accurate and timely data needed to drive more advanced technology improvements.
Let’s take a step back and clarify why such overlooked activities are critical to success.
In technical terms, technologies like artificial intelligence (AI) and business applications like control towers rely extensively on structured data. Structured data is the kind of data that an IoT device produces and stores in neat columns in a database.
However, the context for that structured information is contained in “unstructured” data: documents, forms, emails, communications, etc. It’s in these unstructured, and sometimes uncaptured, data points that errors are so often introduced or wholly ignored through manual processes.
So, while building a dashboard to see the current state of your supply chain is relatively straightforward, it brings limited value because at best, even assuming all the structured data the dashboard/control tower accesses is accurate, the dashboard only shows you symptoms such as delays and bottlenecks. It cannot show you the causes of those delays and bottlenecks, which may stem from errors in uncaptured, unstructured data.
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Document and data errors will always occur, but many are avoidable. And those errors that do appear can be caught and resolved much more quickly with modern supply chain technologies than they can with legacy systems.
Document capture technologies are designed to do this and have been around for decades, but recent advances have significantly improved their capabilities.
Indeed, the ability to liberate documents from their physical form and move them into the digital realm has long yielded benefits in productivity and security while helping to reduce costs.
But more recently, advances in AI and machine learning (ML) combined with relatively mature optical character recognition (OCR) technology have made it possible not only to liberate the document and immediately identify errors and exceptions, but also to liberate the embedded business information required to drive business operations.
These intelligent capture technologies open new possibilities to reimagine traditional supply chain workflows.
Of course, every organization is a little different; even so, benefits of using these tools typically focus on reducing manual and repetitive activities (for example, human key entry work).
Your organization may already scan paper documents, and indeed many of your “documents” may already be digital. However, it’s likely you still undertake a lot of manual key entry work, no matter how sophisticated your organization. And it is here that errors regularly occur, particularly when your staff are keying repetitive data such as quantities, descriptions, dates and addresses into different screens and systems .
Be this information from manifests, BOLs, invoices, packing lists, certificates, etc., manual key entry will by default generate errors.
Modern-day intelligent capture technologies are much more powerful than those of a few years ago. They can dramatically reduce the exception rate and improve the accuracy of document processing tasks, and they can fully automate many activities.
Again, they provide your organization with a fundamental data foundation to enable you to explore using the more advanced technologies flooding the supply chain market.
To be crystal clear, we see immense opportunities for leveraging supply chain technology to improve efficiency, visibility and profitability.
However, there is a logical and immutable order to the steps required. The starting point is always an analysis of the current situation and the remediation of document-based and often manual tasks and processes. Fix these first, and you will be amazed at what technologies like AI and blockchain can deliver.
