Intelligent Orchestration

// what is intelligent orchestration?

I define Intelligent Orchestration as a major shift from human-routed coordination to system-composed decisions across value chains.

Let's look at history first. My personal take is that, for twenty-three centuries or more, hierarchy solved the coordination problem across every kind of operation. There was nothing to choose from - it was the only method available.

But wait, let me clarify first - you won't get another AI-in-supply-chain pitch from me; there are plenty in consulting decks, YouTube channels, and across the World Wide Web.

My message and thesis focus on a single structural shift that will shape our agendas over the next three to four years: the way we run and manage supply chains is changing. This change is fundamental; it's evolving fast and, in some areas, will be quite painful for all actors involved.

This quantum leap isn't happening because of new technology. The main reason is that the constraint that made hierarchy necessary is no longer binding.

I'm happy to debate this topic with other practitioners, as I don't pretend by any means that points of view that follow are any kind of absolute truth. And for any single individual, it's cognitively impossible to grasp each aspect of complex operating systems' drift triggered by substantial changes to their first principles.

But let's return to the point of history and my interpretation of events that brought us to the need to rethink issues of hierarchy, orchestration, and the future of operating models.

The 2,300-Year-Old Routing Problem

I'd like to share some context first. Jack Dorsey and Roelof Botha published From Hierarchy to Intelligence in March of 2026. They came to a conclusion similar to mine - that hierarchy is an information routing protocol and the constraints under which it was built are disappearing. Yet we reach our conclusions from very different points of view. They begin in Rome and analyse the organisational structure of a single business. My analysis begins with Alexander the Great's movement of grain for army needs and jumps forward through time to operations that cross multiple businesses and companies. While their analysis is more centred on the software sector, I work on a thesis about how Intelligent Orchestration is shaping the dynamics of modern value chains and operating models.

Before we used the hierarchy model as a management concept, it was a purely logistical problem.

We must go back to the time of Alexander the Great, when he became emperor of a newly formed region stretching from Greece to India. What fascinates me is that he achieved this not through a new generation of warfare, but through the intelligent application of supply chain principles in their basic form.

Alexander the Great especially stands out for deploying the first structured approach to logistics, and you might recognise some of its forms that have lasted to our era.

It was achieved by pre-positioning supplies along campaign routes and consciously synchronising army marches with local area harvest cycles. Soldiers began using rivers and coastal shipping instead of overland carts, allowing them to disband baggage trains that significantly slowed movement, especially in unfriendly terrain. An army of 40,000 soldiers moved at an unimaginable speed for the ancient world.

His only solution was a multi-layered process of delegation and an informational cascade:

• regional governors who controlled supplies of food and other basic items
• quartermasters who facilitated synchronisation between provinces and
• messengers who connected each node in the army.

While information travelled up the chain of command, decisions flowed downward to lower levels of hierarchy. Indeed, we might argue that each handoff reduced reliability, increased delay (latency), and raised the risk of error or loss of data fidelity. But it worked, given the unbelievable results Alexander achieved during his short lifespan.

But history never stops evolving, and fast-forward, we're facing the walls of the Roman Empire. That's when the empirical principles Alexander the Great discovered were codified into the structure of a war machine that survived for centuries. For example, the Roman Army required:

• a decanus to oversee eight soldiers living in one tent
• a centurion oversaw eighty soldiers
• a legate supervised five thousand soldiers.

It wasn't a question of how many layers were needed - it was a matter of determining whether humans were the only option for those layers to perform their functions.

The same patterns that survived until today appear in any manufacturing operation. In some cases, based on my experience at several processing facilities:

• a foreman was responsible for about eight to fifteen employees
• each foreman reported to one or two shift supervisor(s)
• the plant manager oversaw the shift supervisor(s).

While many refer to this as management theory, I prefer to think of it as an information-routing protocol. To date, I'm aware of no technological solution that has replaced humans operating this routing protocol since it first emerged over twenty-three hundred years ago.

The method Alexander developed to move grain across his empire is being applied today to move products through supply chains.

MRP and the First Planning Layer

In 1806, Napoleon defeated the Prussian army. After learning from this loss, the Prussians introduced a new layer: the General Staff. It consisted of officers who would primarily focus on strategic planning and information coordination. The explicit goal was defined as to "support inept generals" as their talent had been absent.

The operations side of business enjoyed its early success in the 1960s. With the emergence of Material Requirements Planning (MRP), business got a computerised system for integrating production schedules, material needs, and sourcing. This was a significant shift in our domain because, for the first time, a technology started tracking the plan rather than a paper on a clipboard. However, the machine itself couldn't interpret data or react to it. It calculated and gave people the insights necessary to make decisions.

In my opinion, both parts matter: lessons from the history of war, from ancient times to modern military strategies, combined with the evolution of MRP methodologies, shaped much of how we run supply chain operations today, in 2026. This evolution created a set of mental models we need to unlearn to be better positioned to leverage what AI and technology offer today.

For that reason, we also need to distil some first principles of operations that should guide our thinking moving forward. I try to do this with heuristics I observe in my daily reality, without pretending they're universal truths.

But let's continue exploring where all this brings us.

ERP as the Organisational Chart

Daniel McCallum, who worked at the Erie Railroad at that time (the railroad had over 5,000 employees and stretched across 800 kilometres), produced the first organisational chart in the 1850s. He did this alongside a few other engineers (Benjamin H. Latrobe and John E. Thomson, employed by other railroad networks) who dealt with the same issue - reducing railroad freight costs driven by internal operational inefficiencies. The outcome this group achieved: operations became visible and ran through a hierarchy. That was the beginning of corporate structures as we know them today.

When I saw this chart for the first time - it certainly lacked the information and operational detail needed to coordinate railroad activities. But I also recognise that it was a real first systematisation step providing a handful of individuals with a solution to view a complex system that no single person could physically walk through. However, all coordination still came from the people viewing the chart.

ERP had a similar impact with SAP, Oracle, JDA, etc. You can now visualise your organisation's data structure; traverse through your inventory; and trace a purchase order from when it was requisitioned to when it was delivered.

Yet, seeing doesn't necessarily mean knowing. Being able to view your supply chain is very different than orchestrating it. An ERP system provides maps, but those maps don't let anyone drive.

Lean and Six Sigma - Optimising the Routing Layer

Frederick Taylor broke work into specialised tasks, assigned experts, and measured everything. Efficiency through decomposition. Lean and Six Sigma applied the same logic to operations - waste reduction, process control, standardisation, continuous improvement.

Powerful within a stable operating model. Brittle when the world changes. A supply chain optimised for efficiency assumes the environment stays still long enough for the optimisation to pay off. Since 2020, it hasn't.

The human routing layer is faster and leaner, but it's still human.

The Control Tower - Operations Gets Its Matrix

In 1959, McKinsey consultants Gilbert Clee and Alfred di Scipio published the matrix organisation - combining functional specialties with divisional units. Central standards plus local agility. Shell and GE adopted it. It became the "modern" corporation.

Supply chain built its own matrix: the control tower, which the field now calls supply chain orchestration. Demand, supply, logistics, finance - all visible in one room or one screen. Cross-functional, real-time (or near enough), integrated. AI assists, humans validate and approve. APIs connect systems. Anomalies surface before failure.

Better than silos. But still human-routed. The control tower sees everything. It decides nothing autonomously. Every escalation still flows through a person. Every exception waits for a meeting.

The Digital Twin as World Model

Every layer of hierarchy exists because someone, somewhere, needs to ask "what is happening?" and relay the answer to someone who needs to decide. What if the operation itself could answer - continuously, without being asked?

The digital twin isn't a 3D visualisation. It's a decision substrate. A real-time, machine-readable representation of inventory positions, production capacity, demand signals, supplier state, logistics networks, working capital constraints. It replaces information flow through management layers. The twin knows what the control tower operator had to ask about. It doesn't wait to be queried.

A network of specialised agents coordinates across functions without centralised direction. AI-driven within policy guardrails. Humans handle exceptions. The system anticipates and routes around disruption before the S&OP meeting convenes.

The Intelligence Layer - Composing Decisions

This is where intelligent orchestration begins.

The intelligence layer doesn't just observe - it composes. It takes existing capabilities across the value chain and assembles them into responses that no individual planner would have constructed.

A demand signal shifts in Southeast Asia. The intelligence layer recognises the downstream impact on European production three weeks out. It composes a procurement rebalance across two alternative suppliers, a logistics reroute through Rotterdam instead of Antwerp (where port congestion is building), and a working capital adjustment to cover the expedited shipment - all before the weekly planning call.

No supply chain planner decided to trigger that response. The capabilities existed. The intelligence layer recognised the moment and composed them. This is the difference between a system that alerts and a system that acts.

Continuous self-optimisation. Closed-loop execution where action feeds learning and learning refines action. Demand sensing with real-time model retraining. Autonomous contract negotiation within policy bounds. Self-adjusting safety stock across a thousand SKUs.

The Edge - What Stays Human

The edge is the boundary where the intelligence system meets human judgment. Places the model can't reach: intuition, cultural context, trust dynamics, ethical decisions, novel situations, high-stakes calls where the cost of being wrong is existential.

In operations, the edge is where value chain leadership actually matters:

• Supplier relationships - a twenty-year partnership with a grower in Colombia can't be reduced to a risk score
• Crisis judgment - when the Suez is blocked, the model proposes alternatives but a human decides which customers get priority
• Ethical sourcing - the cheapest route isn't always the right route
• Market entry decisions - entering a new geography is a bet, not a calculation
• Talent and culture - building teams that can operate this way requires leadership, not algorithms

"A world model that cannot touch the world is just a database."

Intelligent orchestration doesn't eliminate leadership. It repositions it. Leaders move from the routing layer - where they spent most of their time relaying information, aligning functions, and arbitrating priorities - to the edge, where they do work that only humans can do.