The Goal in Manufacturing Operations Was Never a Single Pane of Glass

Walk the floor of almost any plant and count the screens. The Overall Equipment Effectiveness (OEE) board on the wall, the SCADA station by the line, the maintenance backlog on a supervisor's laptop, the quality report someone exports to a spreadsheet before the morning meeting.

For years, connected manufacturing operations pursued a better way. If only there could be one consolidated view, a single pane of glass where everything finally comes together. Manufacturers keep chasing this dream, but the screens keep multiplying.

That’s because a single pane of glass never should have been the ultimate pursuit in the first place. But that’s what operations teams were told and sold. It’s a simple and overly simplified goal.

Outcomes are the goal. Business transformation, not digital transformation or merely consolidation. A system reconfigured, a defective batch held, a work order created, scrap reduced and all before a person has to notice anything is wrong. A screen, however unified, doesn't do any of that on its own.

Industrial DataOps got the industry most of the way there

Give credit where it's due. Industrial DataOps is the category built by credible players solving a genuinely hard problem: getting raw signals off the floor or out of the supply chain, normalized and contextualized well enough that they mean something. Further, Industrial DataOps providers made integration with downstream MES, SCADA, BI, AI and other industrial platforms even easier. But that's still only integration, and meaningful integration is still a strategy, not a reality.

The 2025 MuleSoft Connectivity Benchmark found the average enterprise is now running 897 applications, with only 29 percent of them integrated. If you isolate OT, the numbers are worse. That ratio doesn't improve on its own. Every new machine, protocol and line on a plant floor adds one more source that was never built to agree with the rest of the stack.

Even solved well, integration just converges on a nicer screen

A raw number from a controller and a raw number from a vibration sensor don't mean anything on their own. The magic happens when DataOps is combined with correlation, aggregation, integration, analysis, business intent and compliance guidelines before, during and after visualization.

Here's the trap: do DataOps well, and what you get is a clean, well-organized, fully contextualized dashboard and a data pipeline to downstream applications. It's better than a single pane of glass, but often the result is just multiple panes in multiple systems connected to the pipes.

Even if you get all your operations into a single pane of glass, how does that actually help individual decision makers in specific plants on a specific line on a specific shift?

A maintenance tech, a quality engineer and a plant manager all staring at the same, beautifully consolidated screen is not solving the problem. They don't need the same view or the same information.

The technician needs a work order with the asset ID and fault code attached. The quality lead needs faulty parts held before the next pallet ships. The manager needs none of that detail and all of the business consequences. One screen serving all three, no matter how well-integrated the data behind it, is a compromise none of them asked for.

Orchestration is what closes the loop

This is why orchestration is the next evolution in the transformation journey. Automation → Integration → Orchestration. 

It’s not a fourth data layer stacked on top of DataOps. It’s what happens when workflows are created from and with Device Operations (DeviceOps), DataOps, and broader system and process Observability. Orchestration also means that data and workflows flow back upstream as well. They enter the control plan and carefully execute command/control actions, configuration changes and much more.

DataOps with integrated wellness monitoring (Observability) determines a machine needs a new configuration, then a workflow executes it. A workflow decides a new signal pattern is worth watching, and a specific Observability policy generates a new dashboard widget, automatically. Business intent and KPIs determine that a reading needs more context downstream. None of these actions waits for a person to be looking at the right screen at the right second. It's a closed loop, not a one-way pipe from signal to screen.

That return path is the whole difference. A dashboard, no matter how unified, has no way to act on a device, rewrite a data pipeline or spin up its own new view. An orchestrated loop, including with Human-in-the-Loop workflows, can do all three, and it does them at the speed the machines set, not the speed a supervisor can read and interpret a dashboard.

What a closed loop is worth - the value of Orchestration

Unplanned downtime is not a minor line item. ABB's 2023 Value of Reliability survey, drawn from more than 3,200 plant maintenance leaders, put the global median cost of a single hour of unplanned downtime near $125,000. A more recent Fluke Corporation survey found 61 percent of manufacturers were hit by unplanned downtime in the past year, at a cost the researchers put as high as $852 million a week across the sector surveyed.

Those numbers don't show where in the process the money leaks. But they make the stakes concrete. A screen that requires a person to notice, interpret, and act is a screen with a delay built into it by design. Orchestration removes that delay and the need for humans to review, interpret and act on dashboards.

The operations that pull ahead

The organizations that pull ahead over the next decade won't be the ones with the most impressive screen in the control room. They'll be the ones that convert operational signals into what happens next and do so automatically.

Traditional Industrial DataOps was never wrong about what it set out to do. It's just solving a part of the problem. And, in some ways, leading manufacturers through a maze that just keeps hitting a wall. EdgeIQ Symphony offers a next-gen DataOps solution that is woven into the fabric of a purpose-built orchestration platform. A platform that, by design, enables decisions and actions directly tied to actual business outcomes.