The Evolution of the Digital Supply Chain: What's Next?

colleagues discussing the digital supply chain while on the manufacturing floor

The past few years have seen some exciting developments in the increasing digitization and modernization of the supply chain. Once just a loose network of different technologies that augmented and rested above more traditional processes, the latest evolution of the supply chain has seen it transform into a more efficient, agile, and resilient ecosystem that stands well apart from its predecessors. With a digital supply chain, it’s now easier than ever to communicate across formerly discrete steps, collect real-time data, and make informed decisions for optimizing supplier performance, among many other advances.

How did we get here? A steady drumbeat of technological advances, as well as a renewed focus on collaboration across manufacturing verticals, has helped shape this state of the digital supply chain. You can see much of this progress in the way that our very own platform addresses the challenges of modern supply chain management, in particular the problem of the PLM collaboration gap. That said, there are still opportunities for many manufacturers to continue modernizing their approach to the supply chain and how they collaborate across their digital thread.

With that in mind, let’s take a look at how much the supply chain has changed in recent years, then consider where else it can still go.

Historical Perspective

The history of supply chain management goes back a long way. Some pin it to the start of global shipping networks in the 17th and 18th centuries. Others go even further back, all the way to ancient empires in Rome and Egypt and the logistics they used to transport armies and a vast range of goods. Regardless of where you begin, however, the characteristic these early supply chains all shared is that they were manual. Information had to be documented by hand onto paper, while communication took place in person, then later by phone or fax. As a result, traditional supply chains were slow, fragmented, and often inefficient.

With the advent of the computer era, this began to change. One of the first key advances was the wide adoption of barcoding in the 1970s. Now ubiquitous on nearly every product, barcode technology at the time helped revolutionize inventory management and tracking by providing a standardized way to identify and capture product information. This became especially useful with the rise of spreadsheets, algorithms, and other technology that could help predict logistics issues. Suddenly, the challenges of planning out your supply chain, managing resources, and forecasting were much easier.

These advances continued in the 90s, particularly with the development of Enterprise Resource Planning (ERP) systems. By enabling companies to centralize and manage all of their business processes and functions together, ERPs made it possible for them to streamline their operations, improve visibility, and make data-driven decisions across their supply chains. It also opened the door for wider automation, further improving productivity and efficiency and making it easier for businesses to scale.

Of course, the most significant advancement in the past 20 years has been the rise of the internet and cloud-based technology. This has helped usher in an era of increased connectivity and communication, allowing companies to access data and analytics in real-time and then make adjustments instantly. 

Current State of Digital Supply Chains

So where are we now? Although the internet has allowed us to connect together multiple aspects of the supply chain and made communication easier than ever, we are still exploring new ways to increase efficiency and visibility. The Internet of Things (IoT) is one way we’re doing this. IoT devices, equipped with RFID tags and other sensors, have become common throughout the digital supply chain, allowing organizations to collect a vast amount of real-time data. This has made it easier to measure inventory levels, assess equipment performance, and stay aware of many other environmental conditions. 

In order to handle all this data, more companies have begun embracing AI technologies, such as machine learning and predictive analytics. Not only do these help ease the burden of interpreting so much supply chain data, they also hold the process of optimizing various aspects of the supply chain. Although still in its infancy in many ways, AI algorithms have already been shown to be adept at analyzing large volumes of data, identifying patterns within them, then using that to forecast demands and help companies make better decisions.

Let’s look at some examples of this in the real world. IoT devices seem to be everywhere these days. For instance, Volvo uses IoT in its factory floors in order to measure machine health and improve the delivery of predictive maintenance. Similarly, Nissan has built an intelligent factory equipped with IoT in order to enhance traceability, improve quality, and reduce human errors. AI is also becoming more common in the supply chain. One notable example is how Amazon uses AI in its robotics to streamline how packages are processed through their warehouses.

However, all of this progress does not come without its challenges. For one, as the number of technology platforms increases, so does the potential of data silos. Across suppliers or even departments, different systems may be preferred for collecting, analyzing, and managing information. If these systems don’t integrate seamlessly, then this can lead to further fragmentation and limited visibility. Overcoming this by attempting to onboard suppliers or other teams onto new platforms can be its own challenge. Not only will there likely be varying levels of technological maturity, but the task of ensuring data compatibility can often be time-consuming and complex. And alongside both of these is the persistent problem of ensuring data security and privacy. Especially with new technologies in play, stakeholders may be wary about sharing sensitive supply chain data, creating another barrier to collaboration.

The PLM Collaboration Gap: Bridging Engineering and the Supply Chain

A particular challenge manufacturers face as they modernize their supply chains is bridging the PLM collaboration gap. What is this? As supply chain technology evolves and up-to-date, real-time information becomes more important to efficient, streamlined operations, there is often a growing disconnect between the engineers and designers who manage that information within their PLM system, and the many stakeholders both inside and outside of the organization who do not. This can result in a gap between those who use PLM frequently, and those who do not.

Far from a simple inconvenience, this gap can create critical obstacles to the efficiencies and productivity improvements that the modern digital supply chain otherwise delivers. For instance, without an effective means to share information with the necessary stakeholders, it may be necessary to use disconnected solutions like email and file sharing applications. In fact, many manufacturers do just this to send PowerPoint files filled with marked-up screenshots of their data. This can slow the exchange of essential technical product data, hurting the production process, causing errors and scrap, and raising costs. 

But bridging the gap between engineers, sourcing/purchasing, and the rest of the supply chain is something we’ve thought about a lot here at Anark. Our platform makes it possible to break down any silos by connecting your PLM data to your larger digital thread. By automating the publishing process with custom recipes, we help ensure that procurement can easily search through and find up-to-date product data without having to ask engineering for it. In turn, by syncing your PLM/PDM data, engineering can quickly and easily share complete, up-to-date product data packages with procurement and suppliers so that everyone has instant, barrier-free access to the data they need.

On top of this, we’ve made collaboration with this data as easy as it can be. Stakeholders can markup data and make comments on top, and even start real-time chats alongside it. Additional files can be shared through a drag-and-drop interface, then all of it packaged up and published for even more collaboration.

Emerging Technologies and Digital Supply Chain Trends

We’ve come a long way from the traditional manual methods of supply chain management that once dominated — but there are still lots of places to go. Technologies that we now consider experimental, like quantum computing, could allow us to further streamline our complex supply chains and discover better ways of delivering products, while AI will undoubtedly continue to advance and help us uncover new business models and revenue streams. Importantly, we also have work to do in order to make our digital supply chain operations more sustainable and ethical, all the way from design to delivery.

Through this journey, we consider it our job to continue helping manufacturers of all types integrate these various advancements into their supply chain. Different technologies and trends may come and go, but effective collaboration will always be key.

Try out a demo to see what Anark can do for you.

About the Author

Patrick Dunfey
Vice President of Marketing and Sales Enablement
Patrick is an accomplished marketing and sales enablement professional who knows that customers are at the heart of every great innovation. He focuses on driving customer satisfaction and business growth through aligned Product-Marketing-Sales programs. He uses digital systems and data-driven approaches to understand, measure and deliver success, resulting in unparalleled customer experiences and value.  Patrick has 20 years of enterprise software expertise, with specialties in CAD, PLM, ERP, AR/VR and IoT. Prior to joining Anark, Patrick developed and taught a business course on XR value strategy, helping companies identify and realize value using virtual, augmented, and mixed reality. During 14 years at PTC, a leading provider of product development software, Patrick led teams responsible for the design, build and launch of an award-winning, state-of-the-art technology experience center resulting in 5X customer meeting growth, and 66% close rates on those meetings; he led the development of a new IoT sales enablement strategy to map business value to enabling technology contributing to 52% YoY IoT revenue growth; and met with over 1000 companies, ranging from SMB to the Fortune 100, to help bridge the gap between technology and customer value. Patrick began his career as a mechanical engineer, working on product design and development projects with Brooks Automation, Arthur D. Little, U.S. Army, Keurig, and others. He earned his Bachelor of Science in Mechanical Engineering from Tufts University.
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