More than three-fourths of supply chain executives are not prepared to observe and predict changes that may disrupt the flow of their business. Part of the problem is that much of it is not automated — these professionals report spending nearly 14 hours a week manually tracking data on inventory and shipments.

That’s the word from a survey of 250 supply chain, inventory, and planning executives, conducted by LeanDNA in collaboration with Wakefield Research.

While most supply chain executives plan to increase investments in proactive supply chain management (92%), over three-fourths (76%) do not currently have a predictive view of supply and demand — interpreting the signals coming in from key points of the process.

For instance, “if a maintenance failure is predicted, where does that signal go?” asks Paul Noble, founder and chief strategy officer for Verusen. “That baton will need to be passed from a sensor to an intelligent system that can cut a transaction, cut a purchase order, and so on and so forth in the same way. It goes back up the supply chain out of the maintenance realm, to raw direct material predictability, as well as logistics and shipping. These automated systems need to alert one another of upcoming needs.”

However, there’s an absence of predictive data that “has companies operating as though they have no data at all,” the LeanDNA survey’s authors state. More than nine in 10 supply chain execs (92%) make gut decisions sometimes or more due to a lack of predictive guidance in their reports.

Across the supply chain sector, there is general agreement that intelligent tracking and management is still not here yet. Many companies are rushing into technology and automation without considering where the value can and should be delivered.

“There is so much talk about automation and AI technologies, yet many have uncertainties as to how to proceed,” says Scott Marsic, group product manager for robotics at Epson America. “There is no reason for a company to boil the ocean and try to do it all. For automation to be effective in the long run, nothing beats a crawl, walk, run approach. Identify a target automation process, build out internal competencies, prove out a concept, and then scale up. It’s a winning approach that pays out in dividends.”

Digital twin technology — which replicates supply-chain processes and movements — may play a vital role in ensuring greater predictive capabilities. More than a third of executives in the LeanDNA survey (37%) have deployed digital twin and other simulation technologies and more than a quarter (26%) have added on to enterprise resource planning software for more functionality, the LeanDNA survey finds.

Dan Mitchell, global director of retail and CPG for SAS, agrees that digital twins will play an important role in supply chain intelligence. “A digital twin allows a supply chain professional to ask, ‘What if we throw a fictitious disruption at the system?’ to see how it reacts. This allows supply chain professionals to pressure test for resiliency.”

More than four in five leaders in the LeanDNA survey (82%) agree that real-time data that does not provide actionable insights for decision-making is a waste of time and energy. While 82% report having some level of a real-time view of supply and demand, less than one in four (24%) have a predictive view.

AI holds great promise to help organizations stay on top of the movement of people and materials. “AI will help organizations understand data and trade signals for demand up and down or across the supply chain,” says Noble. “Trading across those technologies from a supply chain perspective will include trading across entities and within the organization.”

With real-time data that could inform their business decisions, supply chain executives in the LeanDNA survey say they could improve logistics and inventory management (47%), identify changes in demand (45%), and enhance collaboration (44%).

“When you think of AI imperatives for the supply chain, you should be looking for gaps between the digital and physical supply chain,” says Mitchell. “Where there’s no real-time data, there’s opportunity for automation.”

“If your company doesn’t have the real-time data and skills you need, there are plenty of partners and vendors available to help,” Mitchell continues. “For example, think about where you buy your transportation services, factory equipment and distribution center systems. Today it’s all smart equipment powered by IoT sensors that generate a wealth of information you can tap into. Those same vendors can connect you to training opportunities and partners in their broader ecosystem who can help you fill those skill gaps.”

Barriers to using real-time data for supply chain management include the current tech stack not supporting real-time data (44%) and lack of staff skills and training (55%). And upgrading their tech stack doesn’t seem like an option: 48% report their current system is too ingrained, and another 26% believe their organization can’t afford the implementation disruption.

The goal is to be able to see more clearly what ‘s going on across supply chain operations and data exchanges. However, only about two in five (41%) have increased supply chain visibility, especially when it comes to bracing for the next disruptive event.

“Technology is critical – make no mistake about it,” says Epson’s Marsic. “Unfortunately, though, there is no one silver bullet to address operational challenges. Solutions will vary by company as no two operations share the exact operational pain points.”

“Whether looking at AI or robotics, when applied correctly, technology can have a positive impact on making any company more efficient, resilient, and ultimately more competitive,” says Marsic. “And at the end of the day, that’s what we are all looking for – that “edge” that keeps us at the top of our game while concurrently defending against near and long-term risk.”

Staffing supply chain networks and operations also persist as an issue, the LeanDNA survey shows. Just over one-third, 36%, have reskilled their workforce, while 32% partnered with third-party logistics experts.

“Automation is a great tool in helping supply chain operators overcome labor challenges, but the implementation process requires careful consideration and planning,” advises Keith Fisher, the president of Honeywell Intelligrated. “Advanced automation and robotic systems need to be seamlessly integrated with existing software and control systems to achieve optimal performance. Additionally, as labor resources are stretched, retraining employees to operate alongside automation systems has become a greater priority.”



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