Introduction
Many IoT projects prove their value during pilot phases, yet far fewer deliver the same impact at enterprise scale. In this Q&A, Ilan Gluck explains why successful IoT deployments depend as much on operational processes, ownership and change management as on the technology itself.
[IoT Business News] IoT works well in a small, controlled environment. Why is it so hard to scale deployments across the entire business?
[Ilan Gluck] Pilots succeed because they’re controlled. The number of assets is manageable, the people involved are engaged, and it’s relatively easy to respond to every alert or exception. Once that same deployment expands across hundreds or thousands of assets, dozens of locations, and multiple teams, the operating environment becomes far more complex.
As that complexity grows, technology alone isn’t enough to keep a deployment moving forward. Organizations need clear ownership, repeatable processes, and teams that know how to respond to the information being generated. Without that foundation, dashboards become background noise, alerts get ignored, and visibility never translates into operational improvement.
When organizations struggle after the pilot phase, what’s usually breaking? Is it the technology, or something else entirely?
Managing tens of thousands of devices across hundreds of sites is not trivial. Enterprises need middleware and device management to keep hardware performing as expected throughout the program’s life and to catch issues before they disrupt data.
Get that layer right, and the hardware usually does exactly what it’s supposed to do. But the bigger challenge is often making sure the information it generates becomes part of everyday decision-making.
A pilot succeeds because it’s small enough that a handful of engaged people can make it work through sheer attention. Someone is checking the dashboard every morning. Someone is following up when a pallet sits too long. That works at one site, five sites, or even ten.
Scale changes the equation. By the time you’re managing hundreds of sites, those manual habits no longer hold. Success depends on having clear ownership, defined response procedures, and workflows that make acting on the data routine rather than optional. Without that operational foundation, adoption slows, and the value of the deployment starts to plateau.
The organizations that scale successfully treat IoT as part of how they operate every day. The technology provides the visibility, but it’s the processes around it that turn those insights into better decisions.
You’ve worked with organizations deploying IoT across thousands of assets. What are some of the first warning signs that a deployment isn’t being operationalized successfully?
The clearest sign is when the technology is working perfectly, and nothing downstream is changing. When the same problems keep showing up week after week, it usually means the data isn’t reaching the people who can act on it, or no one has defined what “acting on it” looks like.
Another signal is uneven adoption across near-identical locations. If one site changes how it operates because of the data and a nearly identical site down the road ignores it, that’s a process and accountability gap, not a technology one, and it gets more expensive the longer it goes unaddressed.
Companies often assume that more visibility automatically leads to better decisions. Why doesn’t access to more data necessarily translate into action?
Visibility answers what happened. It doesn’t automatically answer who needs to respond or what should happen next.
Take a pallet that never made it onto a trailer. Detecting that it’s sitting in a staging area is valuable, but unless someone is responsible for investigating and resolving that exception, the alert doesn’t change the outcome.
Adding more sensors doesn’t solve that problem; it just creates more information. Data only creates value when it’s tied to clear ownership, defined workflows, and people who are expected to act on it.
Who needs to be involved to make an IoT deployment successful at scale? Is this ultimately an IT initiative, an operations initiative, or something that has to be led from the top?
All three, and deployments that stall are usually missing one of them. IT enables the deployment by integrating the technology and ensuring reliable data flows. Operations determines how that information gets incorporated into day-to-day decision-making. Leadership provides the direction and accountability needed to make those new ways of working stick.
The organizations that scale successfully treat IoT as a change management initiative, not simply a technology project. When each group understands its role, adoption becomes part of everyday operations.
What separates the organizations that successfully embed IoT into everyday operations from those that never move beyond dashboards and alerts?
The difference is whether using the data becomes part of how the business operates.
Successful organizations build IoT insights into existing workflows, whether that’s how a shift begins, how managers review performance, or how teams prioritize daily tasks. The technology becomes another input into routine decision-making rather than a separate dashboard someone remembers to check.
Organizations that struggle often assume deployment ends when the hardware is installed and the platform goes live. In reality, that’s when the work of adoption begins.
For organizations preparing to scale an IoT deployment, what should they be doing before they expand beyond the pilot to avoid these pitfalls?
Don’t use a pilot solely to prove the technology works. In most cases, that’s the easiest part.
A successful pilot should also answer operational questions. Who owns each alert? What actions should different events trigger? Do those new processes actually improve outcomes? It’s far easier to refine those workflows at one location than after expanding to hundreds of sites.
It’s also important to establish ownership for change management early. A technology partner can help deploy the solution, but adoption has to come from within the organization. The companies that scale most successfully recognize that rolling out devices is only the beginning. Long-term success comes from changing how the business operates.
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