Fueled by new technologies, the future of supply chains is here

Next-gen technologies point way to future of supply chains

The dream is a fully transparent, semi-automated, real-time supply chain -- one that provides true end-to-end visibility and traceability, and places a premium on resiliency to deliver a competitive advantage.

Jai Suri

"Where we've seen the big shift in thinking is how to evolve the supply chain to become more resilient and to have the ability to make decisions in a much more dynamic way," said Jai Suri, vice president of IoT and blockchain application development at Oracle. "That's where technology plays a really strong role."

Here are the technologies that experts said will be essential in building the future supply chain.

IIoT, sensors and data collection

You can't talk about end-to-end visibility and predictive decision-making without data, which is the lifeblood of supply chain modernization. As companies face mounting pressure to deliver the right goods to the right place at the right time, the use of data-collecting sensors is expected to grow. Sensors deployed across manufacturing, logistics and point-of-sale operations will provide real-time information streams that can then be used to automate processes and deliver predictive insights by harnessing AI, machine learning and advanced analytics tools. Figure 1 shows one such application already in wide use among tire manufacturers. 

A decrease in the cost of IoT sensors is already spurring new applications. Manufacturers are beginning to develop digital twins -- virtual representatives of products and processes -- which provide invaluable insights into how a piece of factory equipment or a consumer product is performing in the field. Through use of digital twins, manufacturers gain visibility across the product lifecycle, which in turn leads to a keener understanding of everything from the genesis of a particular quality glitch to the operating performance of equipment.

IoT's ability to enable real-time condition monitoring can also have a profound effect on optimizing warehousing and transportation. Take the example of COVID-19 vaccines, which need to be maintained at a strict temperature throughout their journey. Through a network of sensors in trucks, refrigeration equipment and even vaccine packaging, temperatures can be monitored in real time throughout transport, allowing manufacturers to make on-the-fly adjustments when necessary. For instance, when alerted to a refrigeration problem, a driver could be instructed to reroute the shipment to satisfy another order that's geographically closer or return to a maintenance hub before the contents are spoiled.

"Understanding the status of machines, shipments, delays or cargo helps us be more resilient and adapt to issues," said Oracle's Suri. "If we know a shipment will be delayed or cargo spoiled, we can figure out how to prevent it and make better decisions."

Stefano Mariani

Alcar Ruote, a Switzerland-based manufacturer of steel and alloy wheels, has been experimenting with Oracle Cloud IoT Intelligent Applications to keep tabs on operational performance and production line quality for its factory that produces steel wheel rims for automotive manufacturers. The deployment of IoT, part of a broader rollout of the Oracle Cloud SCM suite, has made it easier for the manufacturer to automate processes and react in real time to any deviations from the standards for its factory machinery, according to Stefano Mariani, Alcar Ruote's head of IT.

After the pilot's early success, and thanks to the flexibility of an all-encompassing REST API library, the group has expanded its use of the IoT apps across paint and assembly lines and ultimately to the broader factory. It is also starting to layer machine learning and AI features on top to anticipate future issues with machines and reduce ongoing maintenance costs.

"With the Oracle IoT solutions capturing, computing and reacting to data in real time, we're able to operate with a high level of flexibility when something changes," Mariani said.

AI, machine learning, analytics integral to the future of supply chains

Data is only as good as what you can do with it, and that's where AI, machine learning and advanced analytics come into play. The technologies deliver on the promise of complete supply chain visibility with their ability to churn through a deluge of diverse data, find patterns, evaluate tradeoffs and scenarios, and automate a response in near real time -- or arm their human counterparts with predictive insights that lead to better decision-making.

Richard Howells

"There's no point in having data if you can't do anything with it," said Richard Howells, vice president of digital supply chains at SAP. "You have to put data into a business context in order to drive improved business decisions and automate business processes."

Advanced analytics could allow manufacturers to use IoT data coupled with data from enterprise systems such as ERP to optimize the throughput of plant floor machinery -- adjusting speed, for example, to lower defect ratios on parts. In IoT-enabled plants, the data culled from inventory and warehouse systems could also be analyzed to calibrate robots to pick or put away in the optimal sequence, Howells explained.

Predictive analytics, fueled by AI and machine learning, could also be used to make recommendations on exactly when to service equipment to prevent system failure and downtime as opposed to sticking with a set maintenance schedule, which might be costly overkill, or conversely, insufficient and reactive.

"It allows you to schedule maintenance so you don't slow down manufacturing or put orders at risk," he said.

But while companies like to talk big about what's possible with AI, they won't get far if they don't have enough high-quality data. That requires investing not just in AI tools, but in supporting technologies such as cloud-to-cloud integration platforms and open APIs, according to Sean Riley, global industry director for manufacturing and transportation at Software AG.

Anupam Khare

Oshkosh Corp., a manufacturer of specialty trucks and industrial equipment, has been ramping up its use of predictive analytics to do continuous monitoring of its global supplier network and minimize disruptions due to COVID-19.

"We've brought all these insights into the light and created visibility so our supply chain team can take action if a supplier is having a problem," said Anupam Khare, the company's senior vice president and CIO of digital technology. "It creates proactive awareness of our suppliers in the context of their own factories, the community or country where they are, and the COVID situation."

The outcome? Oshkosh has experienced minimal supply chain disruptions, Khare said.

3D printing and local manufacturing

Overreliance on China and global regions that offer cheap labor and other advantages was thrown for a loop when COVID-19 hit and production was constricted. In response, companies are now looking at creating a more geographically friendly model that relies on a network of local factories that are closer to the demand, thereby decreasing the time it takes to source parts and allowing more on-demand manufacturing.

"The pandemic forced organizations to think about the need to create a local supply chain to balance the shocks from the global supply chain," said Prasad Satyavolu, a managing director at Accenture interviewed when he was Cognizant's chief digital officer. "Costs may go up, but it's needed, and that has a lot of implications from a technology standpoint."

One technology poised to make a big difference in supply chain localization is 3D printing. Advances in materials, coupled with less expensive but more sophisticated industrial 3D printers, are allowing smaller suppliers and manufacturers to produce spare parts and customized components closer to customers.

Andy Kalambi

"The more you federate the production network, the more you are able to create certain tolerance and risk avoidance," said Andy Kalambi, president and CEO of Rize, a manufacturer of industrial 3D printers.

A digital manufacturing process like 3D printing can also provide a cost-effective way to produce highly personalized goods -- custom sneakers or bespoke prosthetics, for example -- compared to conventional methods like injection molding or casting, which take longer and require expensive tooling. The reality, however, is that 3D printing is mostly used to prototype products and may be years away from widespread use in manufacturing.

Multi-enterprise networks

Having a technology platform where upstream and downstream partners can collaborate, share strategies, exchange purchase orders and invoices, and identify and rank new suppliers is critical to gaining access to the granular supply chain data that allows for a quick shifting of gears.

Cloud-based B2B networks, such as the procurement-centric Ariba Network, have been around for decades. But networks like E2open and Infor Nexus that provide more expansive, general-purpose e-commerce and collaboration with suppliers will continue to gain relevance, according to supply chain experts. These multi-enterprise platforms give organizations visibility into the entirety of their supplier ecosystems, which can be an effective way to mitigate disruption and increase agility compared to a more conventional supplier diversification strategy, IDC Manufacturing Insights' Ellis said.

In fact, in its 2020 Supply Chain survey, IDC found that while 85% of companies had strong visibility into their tier 1 suppliers -- those that supply parts directly to them -- the number fell to 25% for subsequent tiers. Ellis expects that to change by 2025, when he estimates half of all manufacturers will achieve extended visibility, resulting in more agile supply chains and a 50% reduction in the impact of supply-side disruptions, he said.

"An enduring point of frustration is the degree to which so many manufacturers are flying blind on understanding the subsequent tiers of suppliers," Ellis explained. "They understand tier 1 and maybe tier 2, but not tier 3 and 4 at all."

Intelligent robots

Deployment of robots across the supply chain, but notably on the factory floor and in warehouses and fulfillment centers, will continue to be front and center in supply chain modernization strategies. IDC Manufacturing Insights predicted that by 2022, half of manufacturers will accelerate deployment of service robots to better manage specific operational tasks, leading to 15% cost reductions and improved supply chain responsiveness.

Rich Faulk

Since the COVID-19 outbreak, robotic goods-to-person systems are in particularly high demand, given the steep rise in order volumes and the need to enforce strict social distancing guidelines in warehouses to ensure worker safety. Robots can provide the necessary productivity boost and help workers keep socially distanced, according to Rich Faulk, CEO of Locus Robotics, a maker of intelligent robots aimed at warehouse applications.

Today's intelligent warehouse robots use a blend of hardware, software, AI, machine learning and analytics to help companies manage the performance of their warehouse facilities -- from predicting where they'll need to apply labor hours to optimizing order pools for picking efficiency.

"Before, warehouse workers had to walk anywhere from 12 to 15 miles a day. Now they're walking between one and two miles," he said.

Other supply chain technologies in the spotlight

Beyond those mainstays, a handful of other technologies are being called out by experts as likely to play an important role in the future of the supply chain.

Blockchain has been widely heralded as a way to build trust and create traceability across a supplier ecosystem through its ability to record price, date, location, quality and other critical information in a secure and immutable form. Participants benefit from increased visibility of material supplies, a reduction in losses related to counterfeiting and gray market sales, as well as improved compliance over contract manufacturing.

Despite its promise and a handful of semi-high-profile pilots -- including IBM and shipping giant Maersk using blockchain to facilitate cross-border and cross-party transactions, as well as Walmart's freight-payment system (see Figure 2) and numerous initiatives in sustainable food traceability -- there are few supply chain blockchain implementations at scale. The COVID-19 experience may convince some companies to take another look.

"Prior to the pandemic, it was a technology looking for a problem to solve, but we found some uses cases in the last 12 months around traceability," said SAP's Howells. "Blockchain is all about ensuring the integrity of data."

Robotic process automation (RPA) is another technology with potential for automating many of the mundane manual processes associated with supply chain paperwork, such as credit checks, inventory testing and confirmation of receipts. "These are absolutely routine tasks that are killing the productivity of people and they're not creative at all," Satyavolu said. "While many tasks are automated with ERP, there is still a lot of manual work … and all this contributes to latency in the supply chain. And you don't have real-time visibility into what's going on."

Looking further out, digital twins of entire supply chains will aid in transparency and war-room-like scenario planning, while 5G will be essential for feeding bandwidth-hungry applications like digital twins and augmented reality (AR) for training and hands-free work instructions. Control towers are another high-interest area for achieving visibility across the entire supply chain environment, with the latest iteration having the potential to expand decision-making and action beyond the current focus on immediate trading partners. However, experts like Gartner see hurdles to the supply chain control tower concept, given the functionally siloed nature of most supply chains and the cultural and change management challenges associated with creating a digital twin of a supply chain.

Supply chain challenges on the horizon

While the COVID-19 experience has accelerated supply chain digitization, challenges persist. Restricted budgets in a tight economy remain a problem, given that many supply chain initiatives require significant capital investment in equipment -- for example, automated guided vehicles, robots and network infrastructure. Legacy systems, many still in use and not earmarked for replacement anytime soon, create significant integration challenges, especially when you're trying to mash up data to create true end-to-end visibility.

[We've] created visibility so our supply chain team can take action if a supplier is having a problem.

Culture is a huge issue, as the supply chain has historically operated as a functional silo and managers have gotten pretty accustomed to doing things the way they've always been done. Plant floor and warehouse systems, which are considered operational technologies (OT), are generally disconnected from enterprise IT environments and operated as separate fiefdoms, which leads to turf battles between IT and OT. Spearheading holistic supply chain transformation requires a significant focus on change management and skills training, both of which are barriers for many organizations.

Like any digital transformation effort, supply chain modernization has to start with identifying and addressing business challenges -- not pursuing technology for technology's sake. "Start with a business challenge and the business problem you're trying to solve, and back into the technology," advised SAP's Howells.

The future of supply chain management is also not about any single technology, but rather a compilation of capabilities to solve specific business goals. Take freight and logistics optimization as an example: A solution might encompass IIoT, real-time data streams, enterprise planning engines, AI and advanced analytics.

"The big fallacy every supply chain professional needs to come to grips with is that there isn't one single technology," said Accenture's Satyavolu. "Unless you're looking at a convergence of technologies to solve problems, you are not getting results."

While companies are starting to see results -- some of them amplified by work undertaken during COVID-19 -- the level of supply chain digitization is still fairly immature, with most efforts still focused on proofs of concept or pilot projects that have yet to be scaled. Many companies burned by large-scale automation and supply chain projects in the past are leery, but that sentiment is starting to ebb as executives realize what's at stake.

"Our conversations used to be about why someone should put their job on the line to make this investment because it didn't work in the past," said Faulk of Locus Robotics. "Now the conversations are about, 'My job is on the line if we don't do something.' There's been a dramatic shift in the way companies see automation. It's not an option -- it's a mandate."