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The Fan That Taught Me Something About Supply Chains

22 Sep 2026

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In an AI-powered world, the smartest supply chains may be the ones that learn to think beyond themselves.

 

A Simple Fan. A Very Different Way of Thinking.

Recently, I was sitting outside around noon on a particularly hot day. Someone noticed I was sweating and handed me a traditional rotating hand fan. I did what seemed natural: held the handle and moved it back and forth. Left. Right. Left. Right. The breeze felt good. Problem solved. Or so I thought.

Someone sitting nearby smiled and said, “You have to rotate the handle.” I did. And suddenly, the fan made sense. Instead of directing the air back and forth for one person, the fan rotated around its axis and spread the breeze around everyone sitting nearby.

My instinct had been to solve my problem. The design was built to solve a shared problem. That small difference made me think about how we design supply chains.

 

From Intelligent Nodes to an Intelligent Network

Supply chains are full of legitimate, competing objectives. Procurement wants the best price and availability. Planning wants an accurate production plan. Suppliers need enough visibility to secure materials and capacity. Manufacturing wants to avoid interruptions. Finance wants to limit inventory. Sales wants customers to receive what they ordered, when they expect it.

The problem isn't that these objectives are wrong. The problem starts when every participant optimizes its own piece without enough visibility into what is happening around it.

A supplier doesn't fully trust the forecast, so it keeps a buffer. A buyer isn't confident the supplier can respond quickly, so it carries more inventory. Demand changes, but the change reaches upstream slowly. A constraint exists somewhere in the network, but the people who need to know about it discover it only when it becomes urgent.

Then the familiar cycle begins: expedite, escalate, replan, call, email, update a spreadsheet, reconcile another spreadsheet—and carry a little more inventory, just in case. Everyone is protecting the business. Yet collectively, the network can become less efficient.

Very intelligent companies can still make collectively inefficient decisions. That distinction becomes even more important as AI gets better.

 
 

Visibility is Valuable Only When it Changes Action

Most companies don't have an information problem anymore. They have plenty of information. The challenge is that information often stops at organizational boundaries.

A forecast belongs to one company. A capacity constraint belongs to a supplier. Inventory may sit in another system. An order change may arrive through email. A shipment may be visible to one party but not another. Everyone has information, but not everyone has the same understanding of what is happening.

A forecast is useful only if the people responsible for fulfilling it can prepare for it. Inventory visibility matters only if someone facing a shortage can act on inventory that exists elsewhere. A supplier commitment matters only if the buyer can incorporate it into a realistic plan.

That is why collaboration is more than exchanging data. It is creating a shared view of reality—and using that shared view to make decisions together.

The conversation changes from: “Here is our forecast. Can you meet it?”

to: “Here is what we see coming. What do you see? What can you commit to? Where are the constraints? What can we solve together?”

 

Earlier Visibility Creates Options

This may be the most valuable thing collaboration gives a supply chain: time.

A shortage discovered when production is about to stop is a crisis. The same shortage discovered weeks earlier is a planning problem.

With time, you have choices: find another source, move inventory, change a production sequence, adjust a forecast, work with a supplier on capacity, or make a different customer commitment. Without time, you have expedites.

Better visibility therefore does more than give you more information. It gives you more options—and options are what make a supply chain more resilient.

This is why collaboration needs to move beyond asking suppliers whether they can fulfill today's order. It needs to create visibility into what is coming next, including demand, commitments, constraints and inventory across the network.

 

Then AI Changes the Equation

AI can increasingly detect patterns, anomalies, supply-demand mismatches, inventory risks and capacity constraints that are difficult to identify manually.

That is powerful. But AI can make an individual decision smarter without automatically making the network smarter.

Imagine AI identifies a potential component shortage six weeks from now. The insight may be correct. But if the supplier doesn't see the changing demand, the insight remains trapped inside the buyer's organization. If another supplier has available capacity but cannot see the requirement, that option remains invisible. If inventory exists elsewhere but nobody has visibility to it, the company may still place an expedite.

AI can identify the problem. The network still has to solve it. That is where the next chapter of supply-chain transformation lies—not simply in asking, “What can AI do for my company?” but, “What can AI help all of us do better together?”

 
 

The Implementation Challenge is Bigger Than Connecting Systems

Turning this idea into reality is not simply an integration exercise.

Different organizations have different systems, processes, data structures and levels of readiness. A shared forecast is useful only when the participants trust it. A supplier commitment is useful only when the process can act on it. A network view is valuable only when teams have the accountability and governance to respond.

In practice, successful collaboration requires several pieces to work together:

  • Technology Connection
  • Data Alignment
  • Process Alignment
  • Partner Adoption
  • Clear Accountability

At Smartlinks, this is where we see the real implementation challenge. The hard part is rarely just connecting two systems or exchanging another set of data. It is creating enough shared visibility, trust and accountability for organizations to make better decisions together.

Technology enables the connection. Experience makes the connection useful.

 

Turn The Fan

The fan gave me a simple way to think about the shift.

I could move it back and forth and solve my immediate problem. But its real value came when the motion rotated through the system and the benefit reached everyone around it.

Supply chains need a similar shift:

  • From information flowing in one direction to information moving across the ecosystem.
  • From forecasts being communicated to forecasts being collaboratively shaped.
  • From inventory being held as protection to inventory being intelligently positioned.
  • From discovering shortages to anticipating them.
  • From asking suppliers to react to giving them enough visibility to prepare.

Most importantly: from optimizing the individual node to optimizing the network.

The future of supply chains will not be won simply by the company with the most information or the smartest AI. It will be won by ecosystems where intelligence is shared, decisions are connected and action moves across boundaries.

Because collaboration isn't one person helping everyone else. It is everyone playing their part so that the whole system works better.

Not smarter companies operating independently. Smarter ecosystems working together.

That is what a simple hand fan on a hot afternoon made me think about.

See beyond your boundary. Share before you are asked. Solve before it becomes a crisis.

 

LINSA GODWIN SATHIAMOSES ENTERPRISE ARCHITECT

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