Shekar Natarajan is the founder and CEO of Orchestro.AI.
Hundreds of years ago, two English philosophers wrote about their views on human nature.
In Leviathan, Thomas Hobbes set forth the argument that when “men live without other security than what their own strength and their own invention shall furnish them withal,” there is “continual fear, and danger of violent death; and the life of man, solitary, poor, nasty, brutish, and short.”
By contrast, in the Second Treatise of Government, John Locke posited: “The State of Nature has a Law of Nature to govern it, which obliges every one: And Reason, which is that Law, teaches all Mankind, who will but consult it, that being all equal and independent, no one ought to harm another in his Life, Health, Liberty, or Possessions.”
What was written hundreds of years ago by these two philosophers echoes in the supply chain world of the modern era. Supply chains are human systems. That’s arguably their greatest strength—and also their greatest weakness. People bring creativity and innovation to the table. Yet they also bring with them closed-mindedness and irrationality. However, AI can help counter such pitfalls of human psychology. When human psychology and AI’s insights are combined, supply chain stakeholders can move beyond gut reactions, siloed thinking and other irrational behaviors and, instead, facilitate innovative, systemic thinking.
Irrational Behavior In Supply Chains
From my observations, irrational behavior is common in supply chains, driven by factors such as fear, greed and misaligned incentives. Irrationality can surface at any point in the supply chain cycle.
Consider, for instance, three snack food companies that operate warehouses in the same small town. Each warehouse is, on average, at 50% capacity, but because each company fears the other will learn its trade secrets, they refuse to share space. Ultimately, each company ends up burning money and other resources that it could have saved had fear not been a factor.
Or think about how many carriers might service that same small town. There might be only, say, 20,000 doors to deliver to, but each carrier competes for that limited number of doors, undercutting existing rates to gain greater market share. It’s a race to the bottom.
The bullwhip effect and demand amplification are other manifestations of irrationality in supply chains. A sudden uptick in consumer demand for a product could prompt a retailer to order 10 times the usual number of units for that item, causing other supply chain actors, such as distributors and manufacturers, to increase production. However, demand could just as quickly fall, leaving all parties with excess inventory.
How AI Can Counter Irrational Behaviors In Supply Chains
AI can counter irrational behaviors in supply chains. AI can help the industry move from the world Hobbes wrote about to the one Locke did—away from fear and toward reason.
How? At its core, AI uses advanced analytics, real-time visibility, scenario-planning and autonomous decision-making that enables supply chain stakeholders to get past their biases and gut feelings. AI equips supply chain logistics to work like the internet—open, intelligent and aware.
For one, AI creates the possibility of a new level of interoperable, connected structures that break siloes internally and throughout the entire ecosystem. With AI, supply chain stakeholders can essentially divorce their commercial realities from their operational ones. Consider two carriers (carrier one and carrier two) that need to deliver packages to the same house. They could leverage AI, see that they’re headed to the same address and coordinate so that only carrier one goes there. The customer, however, still gets the customer interface of carrier two, which maintains the customer experience of carrier two.
AI is also adept at pattern recognition, which can power significant coordination. Supply chain stakeholders can leverage AI to identify patterns and anomalies and intervene as needed. That’s the heart of real-time, systemic network planning.
Moreover, when it comes to the supply chain, people, I believe, are more likely to trust other people by proxy—via the mathematical equations someone else made to create an AI solution—than directly trust other people. There are inputs and outputs, and if someone doesn’t like an input or output, they can change the rules of the game because they know how the given AI solution operates.
AI also introduces realism to emotional decision-making. Supply chain stakeholders might feel euphoric about, say, an uptick in consumer demand for certain products, but an AI solution can temper that enthusiasm by analyzing historical data and determining that such demand doesn’t hold weight a large percentage of the time.
Finally, AI can help supply chain stakeholders tap into collective intelligence and collaborate cross-functionally. AI solutions that comb through datasets from the broader ecosystem and connect stakeholders to one another can help companies make more informed and strategic decisions.
The Risks Of AI That Stakeholders Must Be Cognizant Of
Despite its benefits, AI poses serious risks.
For one, supply chain stakeholders should not unquestioningly trust and follow AI. Human judgment is crucial. Data without context, for instance, can lead to disastrous results.
As for the concern that some supply chain leaders might have about losing their companies’ competitive advantage if they use AI, they should keep in mind that their data is their data and their processes are their processes. That makes them unique. With that being said, when stakeholders leverage AI solutions, they should not expose their intellectual property to others.
Additionally, supply chain stakeholders should be cautious about putting all their eggs in one basket when making decisions about AI solutions. AI is rapidly changing, and if stakeholders aren’t careful, they could end up stuck with outdated technology that keeps them behind. On the flip side, however, barring certain circumstances, I don’t recommend that companies reinvent the wheel by creating LLMs from scratch in-house.
Then there’s the notion of visibility—the visibility that AI offers is not enough. It needs to be accompanied by action. Visibility without action means nothing.
Supply chain stakeholders have to strike the right balance between human judgment and AI. If they fail to use AI altogether, they risk creating a Hobbesian supply chain world of chaos. If they oversteer their use of AI or misuse it, they risk the same outcome. It’s by carefully marrying the two that they can turn the future of the supply chain world into a Lockean one of reason.
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