Supply chain disruptions continue to wreak havoc on everything from holiday gift availability to rising prices.

Where are we going from here? Noodle.ai gathered “grandmaster” supply chain experts from leading companies to assess just that and the expanding role of human plus machine intelligence—or augmented intelligence—in supply chain performance.

The overarching prediction of our panel was that supply chain volatility will continue – and the key to nailing supply chain effectiveness is through building capabilities to support decision making in the short- term execution horizon. Since COVID, we experienced pantry-loading by consumers, a stuck tanker in the Suez Canal and a deep freeze in Texas that impacted supply chains everywhere. No one knows what will unfold next year, but heightened volatility, and increasing supply chain complexity, are no longer special events but part of the new normal.

The good news? The pandemic-inspired disruptions forced us to innovate faster than ever, and companies are increasingly deploying new software, tools, and machine intelligence to better manage short-term volatility.

Those that’ll get the best result, our panelists note, are those that combine the brute strength of machines with the intuition and expertise of humans. With machines to crunch data continuously coming in from vast supply chains—mixed with factory floor and distribution channel conditions—human planners will have more information on which to base real-time decisions. In this landscape, short term volatility is not only better managed, but becomes an opportunity to excel.

Here’s other highlights and predictions from our discussion:

  • Short-term planning is its ‘own animal’ and a critical capability for better decisions.

There’s only so much one can control, said Vageesh Mehrotra, VP Customer, Planning & Network Strategies at Kellogg. What will matter more, is how one responds to the unexpected. Long-term planning and short-term response are “two completely distinct things,” Mehrotra said. “There is a role for our longer-term planning, but we still have to be able to respond to the short-term volatility.” With assistance from machine learning tools to rapidly compute data and changes in day-to-day conditions, both inside the factory and outside, supply chain planners will be better informed to make the right choices.

  • Reliance on spread sheets, gut feel, and traditional planning software is falling short.

In supply chains, “volatility has always existed,” said Tim Nall, CIO of Brown-Forman. Even before the pandemic, volatility occurred when competitors launched promotions, for instance, or if spring came early or summer was late. Even then, traditional solutions were falling behind. Then the pandemic hit, and everything changed. Brown-Forman’s restaurant channel, for example, simply “disappeared.” At the same time, consumers now comparison shop online and make minute-by-minute decisions as to what they want and when. Traditional planning tools largely focus on the 3 to 18-month timeframe but it’s really the short-term execution window that matters. Meanwhile, distribution centers are moving away from bulk shipments of cases and pallets sent to replenish stores to more “pick, pack and ship” individual boxes, said Andrew Hogenson, Global Head of Consumer Goods, Retail and Logistics at Infosys Consulting. Also, manufacturers have taken a lot of the excess out of supply chains so “when disruptions happen, we feel that much more immediately,” Hogenson added. The combination of short-term volatility, shifting consumer habits, distribution changes and lean supply chains creates a “much more complex supply chain equation” than ever before, Hogenson said. That equation “can’t be solved” with traditional planning tools, processes and human planners who lack visibility into conditions. “A human can’t do it anymore,” agreed Nall.

  • Merging old and new tools will provide more supply chain visibility.

“You would never drive a car with a blindfold on,” Hogenson says. Yet manufacturers drive blind if they don’t have the right data at the right time to make decisions. Given the increasing complexity of supply chains and consumer demand, adding machine intelligence into the solution will give planners a better job of solving ever shifting supply chain equations. Said Nall, “all of us have operated supply chains on Excel for many, many years, … and now we’re saying there’s a better way, there’s a more efficient way. We’ve shown people the power of zeros and ones—the data we have—and how … having visibility into issues can make you much more efficient.”

  • Quickly adding value with new technology is key to adoption.

Kellogg implemented new supply chain tools in just four months. “We did it quickly. That’s usually not the expectation for a large technology implementation,” says Mehrotra. The fast implementation “helped drive credibility,” with planners that the change would add value. Still, the supply chain faced so much change and, with limited human resources, Kellogg also decided to lean on machine intelligence and automate recommendations for planners. “It was a gasp moment. We were taking that control away,” Mehrotra said. Since then, Kellogg has achieved more value with automated recommendations while also simplifying work for planners. “Creating value and putting wins on the board creates trust and credibility for the planning organization,” Mehrota said. Capturing “return on investment is a key way to test and learn and to sell … the idea that you can take action now and you don’t have to wait for a larger technology implementation, which traditionally would be far more costly and take a much longer period of time,” added Danielle Maurici-Arnone, Chief Digital and Technology Officer of Combe International. Even in today’s highly volatile environment, Kellogg’s new solution boosted forecast improvements. If parts of the supply chain soon stabilize, “imagine what kind of value could be created,” with the combination of human and machine intelligence, Mehrota said.

  • The role of people will become more strategic.

When supply chain planners have more data—and machine learning tools to crunch the data—they’ll have greater visibility into pending risks in products and geographies and can make decisions with more information than simply a gut feel. “Arming supply chain planners with the ability to … capitalize on short term volatility is really powerful,” added Mehrotra. In that scenario, planners become more strategic in improving margins, customer service, top line revenue and more. “They’ll have a (new) level of confidence, and the organization will have more confidence in us.”

  • Supply chain efficiency will help the planet, too.

Companies and consumers aren’t alone in benefiting form a more efficient supply chain. The planet will, too, given reduced fuel consumption, less waste and better utilization of raw materials. To get to zero waste, you must know where and when the waste occurs. “That’s the silver lining in this cloud,” Hogenson said. “This volatility opens up a door of opportunity for us to really drive a better sustainability agenda.” Added Maurici-Arnone: “We’re going to merge digital data and AI to really help reduce waste and improve lives.”

  • Inaction is not an option.

“You can’t continue to try to convince yourself that inaction is going to work,” said Maurici-Arnone. “Change is needed now because consumers are expecting those changes … what’s needed is courage to “embrace that change is happening.”

 

A Win-Win.

With human + machine intelligence, or augmented intelligence, supply chains will get more efficient. There will be less waste, which will help the planet, and reduce costs, enabling more control over higher prices. The pandemic was rough on everyone, but challenges also create opportunities and supply chain leaders will seize on them.

How do these predictions stack up with yours? Listen to the discussion on demand here and judge for yourself. Then, to dive into the Noodle.ai FlowOps product suite for supply chains, click here.