How Industrial IoT Platforms Power Transformation in Industry 4.0

The secret behind digital transformation is that many initiatives fail, a fact highlighted by the Harvard Business Review. Yet companies such as Airbnb, Amazon, Netflix, and Uber have successfully launched platforms that reshape entire markets.

In this context, hundreds of Industrial IoT platforms promise to help manufacturers, utilities, and facilities managers reinvent their businesses. The Industry 4.0 vision harnesses IoT, digital twins, and machine learning to fuel the next industrial revolution.

Schneider Electric’s Chief Digital Officer Hervé Coureil brings a unique perspective. With experience as CFO and CIO, Coureil stresses that Schneider is not interested in building or selling platforms for their own sake. It’s not so much about the platform. It’s about how you impact the world with digital technology. In industry, the magic happens when you leverage the power of platforms, and you apply it using specific subject‑matter expertise.

Martin Davis, Managing Partner at DUNELM Associates Ltd., echoes this view, emphasizing people and processes over pure technology. He says industrial firms should focus on how you do things and how they can be done differently. While technology opens new possibilities, it’s not about the technology. It’s about how you interact with your customers. Davis warns that buying a new IoT platform is not a magic bullet.

Many industrial companies pursue digital enhancement rather than full transformation. Most add digital monitoring to existing products, such as jet‑engine manufacturers selling flight hours instead of engines—a notable exception. A lot of these initiatives are about adding digital products and services to an existing business, e.g., digital monitoring of a physical asset.

Schneider’s digital strategy focuses on solving customer problems, not offering a generic IoT platform. The company deliberately stays narrow, concentrating on energy efficiency and sustainability across data centers, electric power distribution, buildings, and industrial processes.

Resource allocation is often overlooked in digital transformation. Coureil stresses the need for a clear decision process and transparent cost accounting. Schneider’s 3,000‑employee digital organization operates as a global cost center, with no chargebacks, which simplifies evaluating the success of initiatives and sharpens prioritization.

Scaling is the real challenge. A demo may look impressive, but how do you run that in 80 countries? How do you scale that to that many plants and keep performance 24/7?

There is a growing trend toward complementing rather than replacing legacy equipment. Companies are becoming wary of ambitious projects that suggest sweeping replacements, preferring incremental capability building.

Predictive maintenance has been hyped, but Bain’s report Beyond Proofs of Concept: Scaling the Industrial IoT shows it is harder than expected, with challenges in extracting actionable insights from data.

Despite the difficulty, Davis notes the payoff is substantial. Many organizations still focus on preventive maintenance, while moving toward condition‑based maintenance offers a more achievable path. There are a lot of opportunities there that companies are not realizing.

A major hurdle is data integration. An IoT platform alone creates data islands; to achieve results, all relevant data must converge in one place. The existing historian or feeding legacy sources into the platform can provide that unified view.

Predictive maintenance initiatives must rest on solid business rationale. If zero downtime is critical, neural‑net‑based predictions can justify the investment. For less critical, discrete processes, a phased approach may be more appropriate. Ultimately, the investment decision should hinge on the best return on resources.