Why Coordination Is the Real Bottleneck in Industry

Why real gains in mining and manufacturing will be from how we orchestrate machines, not machines themselves.

The Mirage of Capacity

In 2025, the request most heard across any mine site or plant floor will most likely be, “more throughput.” This request has been rationalized for decades of investment in new equipment, control systems, automation, platforms, and IoT infrastructure. With the advances of AI-powered operations, a new uncomfortable reality is becoming apparent.

We do not have a capacity issue. We have a coordination issue.

There is a glaring gap in industrial performance relative to the investments made in digitization. In mining, equipment utilization is on average below 65% at digitally advanced sites (PwC, 2024). In manufacturing, only 24% of firms have real-time visibility of production and logistic workflows, despite the proliferation of ERP and MES systems (BCG, 2025). Why is that?

Because when there is no orchestration, visibility is just noise.

Data, Disconnected

Today’s mines and factories are capturing copious amounts of data - from haul cycles, to shift performance, to weather, operator input, variance, and maintenance logs. Unfortunately, most of this data is isolated within SCADA, PLC’s, fleet systems, third party dashboards, and spreadsheets. The result is a sort of digital paralysis. Teams are overwhelmed by the volume of data but are forced to make decisions based on gut feel or conduct last minute triage.

We have experienced it in the field. In the NTWIST site audit review of a gold mining operation in North America, we experienced a control room with multiple forecasts set up on four screens for mill feed, yet dispatchers continued to make manual overrides based on verbal information released by the shovel operators. Control tech had been developed, but the integration was designed to have no impact on operational control. The challenge was human coordination.

You can see this same pattern in batch manufacturing. While conducting a nScheduler deployment review for a food production facility, we discovered that downtime was routinely handled poorly, and the in-place MES was highly advanced. The information was accessible, but the system was unable to adjust the production order to accommodate changing restrictions, newly arrived at raw materials, or emergency orders. Operators made isolated decisions.

The Isolated Optimization Myth

In the industrial sector, there is an optimization myth that states improvements can be made unit by unit. This is evident with statements such as, “let's reduce truck cycle times,” or “let's minimize changeover on Line 4.”

While adjustments and improvements can be made within a unit, the true value and optimization is discovered through a shift in coordination, and alignment of completely diverse units, teams, and barriers toward a fragile, flexible constraint.

Forward-thinking mining companies are realizing this. For many, grader dispatch is not simply a task allocation challenge. It is the first step in a larger orchestration challenge. The goal is more than just the improvement of task assignments. The goal is the creation of an intelligent, integrated layer of the operation that will aid blending and assist in the trace and reconciliation processes. For these mining companies, these solutions are valuable from an operational and strategic standpoint.

At several end-of-life mines, we have seen leaders investigate the possibility of achieving previously untapped capacity in downstream processing, using better coordination instead of additional investment. It is not about the processing tools at your disposal; it is about the orchestration of those tools.

Coordination at Scale Requires Intelligence

Adding more dashboards to a system is not coordination. More meetings and more rules are not coordination.

You coordinate by building intelligence to the system.

That means systems that:

This is what modern industrial performance demands and is what we build at NTWIST.

Intelligence Without Execution Stagnates Progress

The digitization of industry has posed a significant threat to businesses operating on the false logic of visibility achieving control. The investment in sensors or dashboards, or even data platforms, creates the expectation of a transformative program, when in fact very little changes in the KPIs. Why is that?

The answer is simple: there is a significant difference between knowledge and the ability to act.

A study conducted by the Boston Consulting Group in 2025 revealed that 68% of industrial organizations reported limited to no observable improvement to operations after implementing advanced digital platforms. The main reason cited for this was the absence of integration between data and the execution layer (BCG, 2025).

This is easily observed in the many time-critical decisions of operations, such as adjusting shift plans, the movement of materials, and responding to the limitations of equipment. When teams lack shared logic for the levels of priority, delays become a crisis.

From Lists of Priorities to AI Decision Architecture

Closing the gap is going to require much more than AI predictive models. Systems of AI have to dynamically and instantaneously adjust, recommend, and rank priorities.

In our implementation of nScheduler on a mixed-production manufacturing site, dynamic scheduling of constraints resulted in an increase in overall system throughput of 25%. The improvements in system throughput were the result of a reshuffle of orders and materials rather than changes to machine operation speeds.

Why Mines Struggle with Real-Time Coordination

Mines have even greater challenges due to long feedback loops, significant variability in the materials, and a lack of linearity in process dependency. It's less about making the system responsive, and more about integrating the ability to foresee complexity into the system, along with the ability to coordinate across disparate systems that were never designed to work in concert.

Foresighted operations begin to realize this vision by grouping systems like dispatch, blending, and load management into a single system, rather than treating them as unique tools.

The Manufacturing Parallel

Compared to the rugged and non-linear world of mining, the world of manufacturing is characterized by very high variability, speed, and frequent changes to production; this is true for batch and discrete manufacturing.

According to a 2025 Frost & Sullivan report, 82% of mid-sized manufacturers reported digitizing part of their planning workflows; however, only 19% reported using real-time, AI-driven scheduling (Frost & Sullivan, 2025).

The focus here is on integrating, not digitizing.

Point Solutions Can’t Jointly Coordinate a System

One of the most frequent errors we have seen across different industries is the use of unintegrated, highly valued tools. This may manifest as an asset health dashboard, a stockpile tracking app, or a standalone scheduling module within an ERP.

When we speak to operational leaders, the same thing is repeatedly said. Specifically, “Our tools are functional, but we don’t have the integration.” When dispatching, planning, and quality decisions are based on different logical frameworks, the resultant system is not agile, but rather contradictory.

For this reason, NTWIST builds “not one more tool.” All our modules, from nGeoMet-AI to nScheduler), are built to integrate with the rest of the modules in the design layer.

Future Proofing Coordination

Coordination is a capability that is built and maintained over a long period of time. This is more than a software issue.

Leading-edge companies see coordination as a market differentiator. They embed AI into operational rhythms. They do checkups on the system, but they also do checkups on the quality and the lag of the decisions. They go beyond measuring the uptime of the system. They examine how fast the business can fix its problems when the system is down.

Conclusion: Orchestrate or Obsolete

The industrial market is not short on innovation. It has a surplus. The constraint is coordination.

We are addressing just this issue. NTWIST has the vision to create systems that not just see - but act. That doesn't just track - but synchronizes. That doesn't just predict - but prioritize - in every corner of your operation.

NTWIST has a solution to the constraint of coordination.

People Also Ask (FAQs)

What is coordination in industrial operations?

This means that each component of an operation (people, machinery, processes, systems, data, etc.) is working in a unified manner to operate the system as intended.

Why is coordination valued more than equipment capacity?

In contemporary times, the equipment can achieve the desired functions. However, if systems and teams are poorly coordinated, the potential of the equipment will be wasted and make the operation inefficient and cause delays.

How does AI improve manufacturing coordination?

AI assists in prioritizing, recommending, and adaptively modifying operational choices throughout the production process considering variable constraints in real-time.

What causes poor coordination in mining operations?

A combination of disconnected systems, siloed data, and/or manual decision-making, and poor or no integration between operational technologies can cause poor coordination in mining operations.

How does NTWIST improve industrial coordination?

NTWIST constructs intelligent decision-support systems that link planning, scheduling, and dispatch along with operational workflows. This assists in real-time industrial operational coordination.